56 jobs found

We believe in better. And we make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. What you'll do We are seeking a highly skilled Senior Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high volume data processing and real time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications in production settings. Exceptional communication and analytical problem solving skills. Proven successful experience in mentoring less experienced engineers to improve their technical skills. A Typical Day at the Office When you come in, you can grab a coffee or a bit of breakfast from one of the many subsidised cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime, you've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup - whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective. Global OTT Technology Our team develops and supports market leading video streaming services, underpinned by state of the art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport. The rewards Sky Q, for the TV you love all in one place The magic of Sky Glass at an exclusive rate A generous pension package Private healthcare Discounted mobile and broadband A wide range of Sky VIP rewards and experiences Inclusion & how you'll work We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You'll find out more about what hybrid working looks like for your role later on in the recruitment process. Your office space Osterley Our Osterley Campus is a 10 minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers. On campus, you'll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. Other Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.

Summary Apple is a place where you can build incredible products that affect the whole world. Its a place where every detail matters, where we obsess about the experience, and where everything is about surprising and delighting the customer. The Photos app is one of these iconic Apple experiences. Join the Photos UI team - the group that builds all the experiences for Photos, across iOS, iPadOS, and macOS. The Cambridge Photos UI team's focus is crafting deeply personal relive experiences, like Creation of Memories, Featured Photos, and the Photos Widget. We leverage cutting edge AI to help users rediscover and enjoy their most precious moments, and are pioneering new frontiers in Apple Intelligence. We're looking for a Senior Software Engineer who can lead rapid prototyping and architecture for the next generation of Photos + AI features. You will play a pivotal role in the team, at the intersection of UI exploration, design with AI, and large scale photo libraries. Description In this influential role, you will be instrumental in leading the design, prototyping, and development of innovative user interfaces and experiences for the Photos app and related media centric features. You will spearhead the creation of novel AI driven experiences, leveraging Apple Intelligence models to build intuitive, engaging, and visually stunning interactions. Your responsibilities will include architecting robust and scalable solutions, collaborating closely with design, AI/ML specialists, research scientists, and other engineering teams to translate ambitious concepts into polished, shippable features. You will work across the full product cycle, from ideation and rapid prototyping, often using SwiftUI, to delivering high performance, high quality code for features that reach hundreds of millions of users. We are seeking a seasoned engineer passionate about building beautiful UIs, exploring innovative AI applications, and pushing the boundaries of how technology can enhance emotional connection and user delight with their photo and video libraries. You will mentor junior engineers, drive technical decisions, and contribute to the team's strategic direction. Minimum Qualifications Proven experience architecting and delivering complex, user facing applications with a strong focus on the user interface. Demonstrated ability to integrate machine learning models or AI driven logic into polished, consumer facing product features. Experience leading the technical design and architecture of new features, from concept and prototyping through to release. A strong foundation in software engineering principles, including data structures, software architecture, and a proven ability to solve complex problems within a cross functional team. Preferred Qualifications Expertise with modern, declarative UI frameworks (e.g., SwiftUI) to build sophisticated and performant interfaces. Experience with media or graphics rendering pipelines and frameworks (e.g., AVKit, Core Animation, Metal). A track record of analyzing and optimizing application performance, particularly for media heavy or computationally intensive features. Demonstrated success in mentoring and providing technical guidance to other engineers. A history of shipping and iterating on multiple high impact, consumer facing applications at a large scale. A strong passion for photography, visual storytelling, and crafting emotionally resonant digital products. At Apple, we're not all the same. And that's our greatest strength. We draw on the differences in who we are, what we've experienced, and how we think. Because to create products that serve everyone, we believe in including everyone. Therefore, we are committed to treating all applicants fairly and equally. As a registered Disability Confident employer, we will work with applicants to make any reasonable accommodations. Apple will consider for employment all qualified applicants with criminal backgrounds in a manner consistent with applicable law. At Apple, we believe accessibility is a fundamental human right. You'll find that idea reflected in everything here - in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong. Learn about accessibility in Apple's workplace. Role Number:

Why Here? Sainsbury's stands as one of the UK's leading retailers, committed to delivering quality products and exceptional customer experiences across its vast network. The Customer Data Science team within the Data Science Hub develops sophisticated systems for personalised customer decisioning. They leverage rich data assets and advanced machine learning to personalise offers, recommendations, and digital experiences at scale. What Will You Do? As a Senior Data Scientist - Technical Specialist at Sainsbury's, you will tackle ambiguous high-value problems in customer understanding, personalisation, optimisation, and decisioning. You will define and embed best practices across modelling, experimentation, deployment, and model lifecycle management to raise technical standards. Additionally, you will coach through pairing on code and demonstrating standards while representing team needs to the Platform team for better ML Ops support.

Salary: Competitive Plus Benefits Location: London Store Support Centre and Home, London, EC1M 6HA Contract type: Permanent Business area: Data & Analytics Closing date: 22 June 2026 Requisition ID: At Sainsbury's, data sits at the heart of how we operate, innovate and serve our customers. Our Data & Analytics team is building a technically advanced, commercially focused and impactful capability, powering our Next Level Strategy and helping to create a Sainsbury's powered by industry leading AI algorithms. We use data, technology and advanced analytics to drive better decisions across the business, from forecasting and optimisation to experimentation, personalisation and machine learning. With one of the richest retail datasets I n the UK and a portfolio spanning Sainsbury's, Argos, Habitat and Nectar, the opportunity to innovate is huge. Here, you'll tackle complex challenges at scale, create measurable impact and grow quickly alongside brilliant colleagues. People who thrive with us combine business understanding, technical expertise and curiosity, with a natural instinct for problem solving. Join us and help shape the future of retail through data and AI. Associate Data Scientist - Hybrid Working - London/Home In Customer Data Science (part of the Data Science Hub), we build the systems behind personalised customer decisioning - from customer segmentations to offer optimisation. We impact millions of customers, bringing them value and earning their loyalty. This team already personalises all of the offers you see in the Nectar app, but now we're growing in ambition and scale. We aim to personalise everything that matters - offers, online recommendations, digital experiences, communications. And we aim to achieve this using our incredible data asset, our rich customer understanding, and state of the art machine learning and AI. This role will work in a team dedicated to personalising our customer experiences, developing new capability while optimising the technology we already have. You'll apply your experience and ideas to design, build, and improve our capabilities - driving value for the customer and the business. What you'll do Solve the hard problems Work on the technical development of algorithms and pipelines that will deliver against our strategic objectives. Iterate our modelling and optimisation capabilities, applying the most appropriate techniques to use for each commercial problem. Embody and improve best practice Align to best practice across modelling, experimentation, deployment, and model lifecycle management. Be an enthusiastic member of our community Bring new ideas for future approaches, including state of the art techniques where appropriate. Understand how our business really works, including by supporting our stores during peak trading periods. Actively contribute to our vibrant Data and Analytics community of over 800 colleagues, providing a view on new techniques and approaches that can drive positive change in wider teams. Who you are We're looking for a highly motivated self starter who owns their own development - you'll know what you don't know, and you'll use the experienced team around you to advance quickly. You need to thrive in a challenging role, and want to balance technical rigour against our need to deliver commercial and customer value. Experience in a Data Science role (or equivalent academic experience). A strong ability to communicate ideas to audiences of varying technical background and seniority. Data Science expertise Strong grounding in statistical modelling and machine learning. Strong understanding of the "how" behind the algorithm; ability to select the right technique for a given objective and avoid pitfalls. Curiosity, scepticism and attention to detail regarding data quality, samples, bias and ethics. Extensive programming ability across Python and strong ability to use SQL, with a proven experience of building working ML. Understanding of working with production codebases, such as version control. Development A strong awareness and understanding of technology trends and direction in Data Science, analytics and AI. Experience in Data Science roles or equivalent academic experience A strong ability to communicate ideas to audiences of varying technical background and seniority Strong grounding in statistical modelling and machine learning, including predictive modelling Extensive programming ability across Python and strong ability to use SQL Benefits We are committed to being a truly inclusive retailer so you'll be welcomed whatever you are and wherever you work. Around here, there's always the chance to try something new - whether that's as part of an evolving team or somewhere else across the business - and we take development seriously and promise to support you. We also recognise and celebrate colleagues when they go the extra mile and, where possible, offer flexible working. When you join our team, we'll also offer you an amazing range of benefits. Starting off with a colleague discount, you'll be able to save 10% on your shopping online and in store at Sainsbury's, Argos, TU and Habitat, and we regularly increase the discount to 15% at points during the year. We've also got you covered for your future with our pensions scheme and life cover. You'll also be able to share in our success as you may be eligible for a performance related bonus of up to 5% of salary, depending on how we perform. Your wellbeing is important to us too. You'll receive an annual holiday allowance and you can buy up to an additional week's holiday. We also offer other benefits that will help your money go further such as season ticket loans, cycle to work scheme, health cash plans, salary advance (where you can access some of your pay before pay day) and access to a great range of discounts from hundreds of other retailers. If you ever need it there is also an employee assistance programme. Moments that matter are as important to us as they are to you which is why we give up to 26 weeks' pay for maternity or adoption leave and up to 4 weeks' pay for paternity leave. Please see for a range of our benefits (note, length of service and eligibility criteria may apply).

Location London Address London, England Employment Type Full time Location Type Hybrid Department Machine Learning Our Mission At Carbon Re We're on a mission to cut gigatonnes of carbon emissions from the world's biggest emitting industries, like cement, steel, and glass, by applying cutting edge AI where it matters most. We're a small and growing team of scientists, engineers, and strategic thinkers who care deeply about impact and believe in getting there with good humour and urgency. Our SaaS products help heavy industry optimise operations in real time, cutting costs and carbon today while building the foundation for the next industrial revolution. We are seeking a Senior Machine Learning Engineer to help build the models that underpin these control systems and help us level up our machine learning infrastructure. We don't draw a specific line between engineering and research teams. We operate as one cohesive unit, sharing tech stack, knowledge, and objectives. Our focus spans from fundamental ML research to commercial grade software development, offering diverse learning and impact opportunities. Your main responsibilities Work in the machine learning team as an individual contributor, building, testing and deploying our models. Contribute to technical innovation and problem solving across the machine learning lifecycle. Collaborate with the product team on customer projects, planning, designing and delivering the work packages required, as well as playing a significant role in the development of our wider product. Help establish best practices to improve our internal processes. Contribute to the design and implementation of robust, maintainable and scalable machine learning systems. You will also contribute to our fear free development process by building tooling that helps the team move faster and more sustainably. You will be supported by continuous builds, tests, a constructive review system, and a strong culture of improving engineering processes. What a great fit looks like You have 2 or more years of experience as a machine learning engineer. You are familiar with several ML techniques, and have both theoretical ML knowledge and experience implementing different types of solutions. You are proficient in Python and have a good understanding of the ecosystem of tools and libraries that support ML development (e.g., scikit learn, PyTorch). You have experience working in a scientific environment across disciplines (particularly physics, chemistry, materials science, and engineering), either through previous roles or study. Are passionate about making a positive impact on climate change mitigation and possess a strong interest in our mission. You'll excel if You have prior experience with time series modelling and industrial or IoT data. You have experience in any of: dynamical systems, reinforcement learning, system identification, optimisation or Bayesian statistics. You are used to working in a fast paced startup environment with an agile process. You have a degree in machine learning, physics or chemistry. You are hungry for responsibility, enthusiastic about taking on the design and development of solutions to difficult problems, and eager to drive the progress of new products. You have a solid understanding of modern cloud compute infrastructure as it relates to machine learning, and experience in working with AWS, GCP, Azure, or other vendors. The interview process We run a multiple part interview process. You can choose to interview remotely or on site for some of the interviews, but it's easier to build rapport in person. Intro call - meeting with our talent partner Fundamentals of Machine Learning - a discussion with members of the machine learning team around some of the fundamentals of ML and your understanding and application of them. (1 hour, remote) Technical interview - (half day, in person/remote) Problem solving - applying machine learning, scientific understanding and problem solving to some of the challenges we tackle day to day in the ML team. Engineering - a practical exercise focused on software engineering for ML. Architecture - a discussion based exercise around systems design for ML. Behaviours and Operating Principles - a meeting with two members of our team to discuss your past experiences, to understand how you would fit in with our operating principles. (1 hour, remote) Meet the exec - an informal chat to meet either Josh (CEO) or Buffy (COO) (30 minutes, in person/remote) In the same way we reference check our candidates before making final offers, we invite you to reference check us by chatting informally with any team members you didn't meet during the hiring process. Once the interviews are over, we'll try to make a decision as quickly as possible, and you can ask us for feedback at any stage. In return for your hard work, we'll give you Equity in the company: When we win, you win. You'll get share options, so you're part of our journey from the inside. Flexible working: We trust you to know how and when you work best and to work that out with your team. 30 days of holiday (plus bank holidays). Rest is productive. Take the time you need to recharge. A generous pension scheme: We're planning for the future in more ways than one. Our Operating Principles Go Gig or Go Home: High Bar, All In. What we do matters to humanity, to our customers and to each other. We hold ourselves to an extraordinarily high bar and bring the urgency this mission requires. Concrete Honesty: Be honest. As concrete forms the foundation of our world, genuine honesty and transparency are the bedrock of our culture. Autonomous Ownership: High agency, high ownership. We build systems that take control and make things better. We do the same: see it, own it, drive it. Cement it with Kindness & Fun: Have fun, be kind. We're here to extend Earth's life, but ours is still limited. We want to enjoy the ride.

About Us We are a VC-backed startup focused on hyper-personalisation, currently in stealth. Inspired by the latest in recommender systems, we leverage transformers and graph learning alongside decision-making models to build engaging customer experiences for in-store retail. Our mission is to change retail forever through hyper-personalised shopping experiences that are both simple and beautiful. About the Job We are looking for a Senior Data Scientist with experience in bringing advanced machine learning and data science systems to production to work with our team of industry leading domain experts and engineers. You'll be working across our entire data science stack, from advanced recommender systems to comprehensive performance analytics. Key Responsibilities Design and implement scalable machine learning for complex data analysis, optimised recommendations, and predictive modelling. Translate the latest advances in machine learning into impactful solutions and products, from rapid MVPs to fully deployed, production-ready systems. Bring your models to production and optimise for inference in edge computing environments. Essential Qualifications 3-5+ years implementing advanced data science solutions in a commercial setting. MSc in Computer Science, Machine Learning, or a related field. Experience building data pipelines (realtime or batch) & data quality using modern toolchain (e.g., Apache Spark, Kafka, Airflow, dbt). Strong foundational knowledge of machine learning and deep learning algorithms, including deep neural networks, supervised/unsupervised learning, predictive analysis, and forecasting. Expert-level proficiency in Python, with a demonstrated ability to develop and debug production-grade code. Desired Skills (Bonus Points) Strong practical understanding of retail analytics including consumer segmentations, personalisation systems, campaign effectiveness and media measurement. Experience with recommender systems and/or behavioural AI. What We Offer Opportunity to build technology that will transform millions of shopping experiences. Real ownership and impact in shaping product and company direction. A dynamic, collaborative work environment with cutting-edge ML challenges. Competitive compensation and equity in a rapidly growing company. If you're an energetic data scientist who thrives in a fast-paced environment and wants to make a real impact on the future of retail, we'd love to hear from you.

The Subscriptions Mission builds and scales the products, platforms, and business models that convert free listeners into lifelong Premium subscribers. We focus on driving acquisition, optimizing conversion, improving retention, and delivering seamless commerce experiences that fuel Spotify's growth and bring fans closer to the creators they love. At Spotify, our Subscriptions data powers the decision engines and experiences behind our 700M+ Monthly Active Users and 290M+ Premium subscribers. You'll join a collaborative, cross functional team focused on building the systems that power merchandising, personalization, and seamless subscription experiences at global scale. Together, we shape how users discover value and choose to stay with Spotify. What You Will Do Design, build, and run scalable Java services that power our merchandising platform and support conversion and upsell journeys Work closely with your squad to design backend systems, APIs, and data models on Google Cloud Platform Partner with product managers, data scientists, and engineers to solve meaningful technical challenges Improve and scale data pipelines that support experimentation, heuristics, and machine learning applications Contribute to architecture decisions that improve reliability, performance, and long term maintainability Support production systems end to end, ensuring services are observable, reliable, and continuously improving Share knowledge through code reviews and collaboration, helping strengthen the team's technical practices Who You Are You have 5+ years of experience building backend systems using Java You have strong computer science fundamentals and experience working with distributed systems at scale You have experience designing and operating cloud native services (e.g., GCP or AWS) You are comfortable designing APIs and working with partners to translate needs into scalable solutions You have experience running high volume services in production and understand reliability, observability, and performance You collaborate effectively with cross functional teams and take ownership of complex work from idea to delivery You seek feedback, learn continuously, and look for ways to improve systems and how teams work together You have experience with technologies such as gRPC, BigQuery, Bigtable, CMS integrations, or ML driven systems Where You Will Be This role is based in London, England or Stockholm, Sweden We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home. Learn about life at Spotify Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what's playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward thinking! So bring us your personal experience, your perspectives, and your background. It's in our differences that we will find the power to keep revolutionizing the way the world listens. At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we're here to support you in any way we can. Extensive learning opportunities, through our dedicated team, GreenHouse. Flexible share incentives letting you choose how you share in our success. Global parental leave, six months off - for all new parents. All The Feels, our employee assistance program and self care hub. Flexible public holidays, swap days off according to your values and beliefs.

Introduction A career in IBM Consulting is built on long term client relationships and close collaboration worldwide. You'll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you'll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You'll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long term career development while valuing your unique skills and experiences. Your role and responsibilities As a Senior Data Scientist at IBM, you will lead the design and delivery of AI solutions, advanced analytics and automation for clients across industries. You will work at the intersection of data science, business strategy, and technology, helping clients unlock value from their data assets while mentoring junior team members and shaping IBM's data science capability. Strategic leadership of large end-to-end AI solutions, advanced analytics and automation engagements from discovery to deployment. Act as a trusted advisor to senior client stakeholders, translating business challenges into data driven solutions and articulating the value of AI. Translate complex data into actionable insights and strategic recommendations. Collaborate with cross functional teams including consultants, engineers, and client stakeholders. Design and implement machine learning models, statistical analyses, and AI solutions tailored to client needs. Lead business development through proposal writing, solutioning, and client presentations. Mentor and coach junior data scientists and analysts. Stay current with emerging technologies and methodologies in AI/ML and data science. Required technical and professional expertise Full AI Project Lifecycle: Experience in managing the full AI project lifecycle, from research and prototyping to deployment in production environments in a consulting or enterprise environment. Excellent communication and stakeholder management skills. Advanced Analytics Techniques: Experience with advanced analytics techniques for structured data, including proficiency in Python and AI frameworks such as TensorFlow, PyTorch, Keras, or Hugging Face. NLP and ML Methods: Deep understanding of Natural Language Processing (NLP) and Machine Learning (ML) methods for unstructured content, with expertise in foundation models and large language models. AI Solution Development: Experience in architecting and delivering AI solutions using cutting edge technologies, including tools like Github Copilot and Amazon Code Whisperer. Cloud Platforms and Services: Familiarity with cloud platforms (e.g., Kubernetes, AWS, Azure, GCP, IBM Cloud) and related services, as well as experience with relational and NoSQL databases (SQL, Postgres, DB2, MongoDB). As an equal opportunities' employer, we welcome applications from individuals of all backgrounds. However, for you to be eligible for this role, you must have the valid right to work in the UK. Unfortunately, we do not offer visa sponsorship. Preferred technical and professional experience Foundation in Specialized Areas: Experience with one of the following areas: NLP, Image Processing, Video Processing, Voice Processing, or Watson technologies, enabling optimization of AI solutions and driving business value. Proficiency in Modern UI Frameworks: Familiarity with modern UI frameworks such as Backbone.js, AngularJS, React.js, Ember.js, Bootstrap, and JQuery, allowing for seamless integration with AI solutions. Operating System Knowledge: Experience working with various operating systems, including Linux, Windows, iOS, and Android, facilitating smooth deployment of AI solutions across different environments. PhD or equivalent experience is a plus (preferable in Data Science, Computer Science, Statistics, or a related field. IBM is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.

Spotify's Subscriptions Mission focuses on converting listeners into lifelong subscribers by delivering seamless, valuable experiences across pricing, packaging, and customer journeys. We build the systems and tools that power acquisition, retention, and overall subscription growth at scale. The Messaging Platform powers Spotify's communications to over a billion users - from push notifications to emails and in-app messages that connect listeners to the content they love. Within this space, the Paloma squad focuses on message optimization: deciding which message reaches which user, through which channel, and at what moment. We're evolving how messaging works at Spotify - moving from short-term optimization toward systems that understand long-term user journeys. By combining reinforcement learning approaches with deeper domain signals, we're expanding how machine learning shapes the entire messaging funnel. What You'll Do Design, build, and ship machine learning models that optimize messaging across push, email, and in-app channels Plan and run A/B experiments in a multi-objective environment, balancing conversion, engagement, retention, and reachability Contribute to reinforcement learning systems that optimize for long-term user outcomes rather than immediate interactions Partner with product managers, data scientists, and engineers to define what success looks like and how to measure it Own the full ML lifecycle, from data and modeling to deployment, monitoring, and iteration Integrate ML models with upstream systems, including domain value signals and opportunity generation frameworks Help shape the future of AI assisted development within the team, exploring how tools can accelerate experimentation and delivery Who You Are You have strong experience building and deploying machine learning models in production environments at scale You are comfortable translating business problems into ML solutions and discussing trade offs with cross functional partners You have worked on complex optimization problems such as ranking systems or multi objective decision making You bring hands on experience with PyTorch and distributed systems such as Ray or similar frameworks You understand experimentation deeply and can design reliable tests in environments with interacting metrics You are able to analyze results using approaches like causal inference or metric decomposition when needed You have experience with or curiosity about reinforcement learning and long term optimization systems You enjoy working across disciplines and navigating ambiguity while shaping strategy and direction Where You'll Be This role is based in London and Stockholm We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what's playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward thinking! So bring us your personal experience, your perspectives, and your background. It's in our differences that we will find the power to keep revolutionizing the way the world listens. At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we're here to support you in any way we can.

We design Spotify's consumer experience-end to end, moment to moment, across every screen, platform, and partner integration. Our mission is to make listening feel effortless, personal, and joyful for billions of users around the world. That means turning complexity into clarity across hundreds of touchpoints-from our mobile and desktop apps to the smart speakers, TVs, cars, and integrations where Spotify shows up every day. If it touches a consumer, we shape it. We bring deep insight into human behavior, design, and technology to craft experiences that feel intuitive, expressive, and unmistakably Spotify. The Verbatim squad sits within the Enrichment & Content Intelligence product area and is focused on helping Spotify better understand audio, text, and visual content through machine learning. The team develops technologies that power experiences across Spotify including content skipping, transcription, moderation, and visual understanding. Working at the intersection of large-scale machine learning and product innovation, the squad partners closely with Product, Engineering, and Data Science teams to build intelligent systems that improve how users experience content across the platform. What You'll Do Lead end-to end machine learning initiatives from ideation and prototyping through experimentation, deployment, and large-scale productionization. Design, develop, and deploy machine learning systems that operate across hundreds of millions of content signals using both real-time and batch processing architectures. Advance Spotify's capabilities in natural language understanding, multimodal AI, and content intelligence. Build and evaluate LLM powered solutions using modern prompting techniques, retrieval systems, and advanced model orchestration approaches. Define rigorous evaluation methodologies including golden datasets, precision and recall frameworks, offline benchmarking, and online experimentation. Partner closely with Product Managers, Engineering Managers, Staff Engineers, and Data Scientists to influence technical strategy and roadmap decisions. Mentor engineers across the organization and help elevate machine learning engineering standards and best practices. Contribute to the adoption of AI assisted development workflows and tooling that improve team productivity and engineering effectiveness. Who You Are You have solid experience developing and deploying machine learning systems in production environments. You have successfully delivered large-scale machine learning architectures operating on substantial datasets and high throughput production systems. You have deep experience with machine learning, deep learning, and modern AI technologies. You have hands on experience working with large language models and understand how to evaluate, adapt, and deploy them effectively for real world product challenges. You have experience building evaluation frameworks and can quantify model performance through robust experimentation and measurement techniques. You know how to navigate ambiguity and make thoughtful technical trade offs that balance product impact, scalability, and engineering quality. You have experience influencing technical direction across cross functional teams and can communicate complex machine learning concepts to diverse audiences. You care about developing others and enjoy mentoring engineers through technical guidance and collaboration. You have experience working with NLP, prompt engineering, retrieval augmented generation (RAG), vector databases, or multimodal machine learning systems. You are curious about emerging AI technologies and excited about integrating tools such as Claude Code, Cursor, and other AI assisted development capabilities into engineering workflows. Where You'll Be This role is based in London or Stockholm. We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.

Location: London Other locations: Anywhere in Region Date: 29 May 2026 Requisition ID: At EY, we're all in to shape your future with confidence. We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. The opportunity The Data Scientist will be responsible for structuring the research question, determining the best analytical approach, conducting analyses, identifying business relevant insights, and creating a compelling story to be communicated to key stakeholders and talent executive leadership. The person will have expertise in data science, with a strong focus on techniques related to text analytics, clustering, time series analysis, multivariate regression, basic predictive modelling, and significance testing. Essential Functions: Utilize data science to conduct research on business topics relevant for digital insights team. Use quantitative and qualitative methods to identify new insights on important issues for digital talent team and wider Talent & SL functional teams. Identify creative approaches to answer research questions. Use your understanding of what is possible with data science to brainstorm creative analytical solutions to test. Rapidly test potential approaches. Stand up simple analyses to demonstrate what's possible and test feasibility. Co develop research plan. Work closely with other Digital team members and business stakeholders to help shape the research approach and potential output. Collect and clean data. Identify relevant data sources (internal and external) and program or leverage existing tools to acquire the data (e.g. SQL, APIs, scrapers, etc.) and test quality. Continuous improvement and creation of predictive modelling taking new levers and environmental factors into account. Work on strategic and operational workforce planning modelling to enable short term and long term planning looking at the impact of offshore, automation, and skills while optimising the cost model. Generate innovative analytical ideas by staying up to date on latest tools and methodologies. Provide subject matter expertise on key domain related topics such as advanced excel, SQL, machine learning, natural language processing, text sentiment analysis, mathematics, statistics etc. Enable the best fit implementation approach leveraging the core and evolving skills in the domain of data analytics, e.g., machine learning, natural language processing, text sentiment analysis. Champion the value of analytics and data driven approach across Talent and provide thought leadership as required on the complete cycle of talent analytics. Design data & insights model to cater to data visualization and be accountable for provision of advanced and predictive analytics to deliver robust analyses and support the delivery of insights to the Talent Executive teams. Perform analyses. Independently conduct rigorous statistical analyses in Python or R. Most research projects will utilize quantitative modelling, statistics, or machine learning (especially text analytics). Identify insights and communicate findings. Create a compelling story that articulates key insights to non technical audiences through PowerPoint and/or Business Intelligence Platforms (e.g. PowerBI) Analytical/Decision Making Responsibilities: Uses scientific methods and technologies to analyse data, develop models and deliver solutions to the business. Data modeling and Management, integration and manipulation of large disparate datasets (i.e. structured, semi structured or unstructured) Translate complex analytical results into actionable recommendations. Knowledge and Skills Requirements: Experience applying a broad range of data science techniques. Key areas include text analytics, clustering, time series analysis, multivariate regression, predictive modelling, and significance testing. Demonstrable understanding of statistics and mathematical concepts relevant to data science. Experience with data wrangling, cleansing, and data engineering for data science applications. Experience in Advanced Data Visualization tools, such as Tableau, Spotfire, Qlikview and others for integration between disparate data sources, design and implementation of KPIs and generation of automatic and scalable visualizations that will facilitate extraction of business insights. Ability to participate effectively in virtual teams and networks across diverse and dispersed geographies. Strong teaming skills; collaborate effectively across talent ecosystem, within the digital team and the firm at large. Strong communication skills for sharing thought leadership across EY and externally to enhance EY reputation. Strong organizational skills and attention to detail - the ability to operate within budget and effective time frames. Strong research and analytical skills to track and interpret trending directions for data analytics and also to identify potential future options. Ability to cope with ambiguity; to drive change and performance outcomes in a complex and agile environment. Supervision Responsibilities: Work closely with the Leads across the Digital and wider Talent Functions to ensure the provision of services that support business and functional delivery. Develop digital capabilities, define key digital competencies for the team, and ensure provision of learning to advance skills Independently maintain and leverage (when appropriate) an internal network, including effective partnerships with senior stakeholders, across EY practices / functions that will enable personal effectiveness in the position Other Requirements: Due to global nature of the role; travel and willingness to work alternative hours will be required. Due to global nature of the role; English language skills - excellent written and verbal communication will be required Job Requirements Education: Educated to degree level Higher professional or masters qualification is preferred, not required Certification Requirements: Higher professional or masters qualification in a related discipline is preferred, not required Active membership in related professional bodies or industry groups is preferred, not required Experience: Significant experience in a closely related Data analytics / data / insights driven role. Experience of developing and implementing operational standards and processes to achieve required outcomes. Experience of having worked on digital analytics design / process or analytical planning and development initiatives. Experience of developing digital capability, defining key digital competencies for the team, and ensuring provision of learning to advance skills. Demonstrable experience of collaborating with talent colleagues to understand needs / requirements and of shaping digital solutions. Demonstrable experience of working with third party vendors / external system implementors to deliver reporting, insights and analytical solutions from design to enablement. Experience of leading and participating in global dispersed teams to enhance services, processes, and standards. Demonstrable experience of working in fast paced, ambiguous, stressful environments to deliver required results. Demonstrable experience of anticipating issues and challenges and proactively working to navigate challenges. Experience of conducting internal and external research and analysis, providing best practices and insights to drive improvements. Demonstrable experience of having worked to lead or provide SMR advice to achieve successful change outcomes What we offer you At EY, we'll develop you with future focused skills and equip you with world class experiences. We'll empower you in a flexible environment, and fuel you and your extraordinary talents in a diverse and inclusive culture of globally connected teams. Learn more. Are you ready to shape your future with confidence? Apply today. To help create the best experience during the recruitment process, please describe any disability related adjustments or accommodations you may need. EY Building a better working world EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets. Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow. EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.

Your roleWhat you'll be doingVP AI & Data PlatformsWhat We NeedCorpay is currently looking to hire a VP AI & Data Platforms within our IVP Commercial team. This position falls under our International Vehicle Payments (IVP) line of business and is located in London, Victoria.You will lead our internal AI, data science and data engineering capabilities across our Europe & Rest of World fleet business unit. This is a senior leadership role focused on turning AI and data into tangible business outcomes - driving growth, improving customer retention, optimising operations and enabling smarter decision-making across the organisation.In this pivotal role you will sit at the intersection of business and technology, working closely with commercial, operational and functional leaders to identify opportunities, deliver impactful solutions and scale AI adoption across the companyYou will report directly to our Chief Commercial Officer, IVP and regularly collaborate with the wider Strategy team, IVP business leaders and supporting teams across Europe and the UK.How We WorkAs a VP AI & Data Platforms , you will be expected to work in an office environment. Corpay will set you up for success by providing:Assigned workspace in Vincent Square, London (Victoria)Company-issued equipmentFormal, hands-on training. Support for you to complete professional certifications.Collaborative and supportive leadershipRole ResponsibilitiesThis is a unique opportunity to shape and scale AI within a global, high-growth business, working directly with senior leadership to embed AI into how the organisation operates day-to-day. You'll have the platform to build, lead and deliver meaningful change - turning data and AI into a core driver of business performance.What you will be delivering;Lead AI & Data StrategyDefine and execute a clear AI and data strategy aligned to business priorities, with a focus on revenue growth, customer retention, operational efficiency and productivity.Identify, prioritise and build a portfolio of high-impact AI and data initiatives.Deliver Business ImpactOwn the end-to-end lifecycle of AI initiatives - from ideation and business case through to delivery, adoption and measurable results.Ensure solutions are embedded into business processes and drive real, sustained impact.Build & Scale Data PlatformsOversee data science, machine learning and data engineering teams to build scalable, reliable and high-quality data and AI platforms.Drive best practices in data architecture, model development, deployment and lifecycle management.Partner Across the BusinessWork closely with Sales, Operations, Finance, Credit, Marketing and Technology teams to translate business needs into data and AI solutions.Act as a trusted advisor to senior stakeholders, bridging the gap between technical teams and commercial leaders.Drive AI Adoption & CapabilityChampion the use of AI across the organisation.Promote practical, day-to-day use of AI tools and solutions, and help teams unlock productivity and better decision-making.Support training, upskilling and knowledge sharing to build a data-driven culture.Lead & Inspire a High-Performing TeamLead a multidisciplinary team of data scientists, ML engineers, data engineers and analysts.Build a strong, collaborative and innovative team culture focused on delivery and impact.What We're Looking ForExperience & ExpertiseProven experience leading AI, data science, machine learning or data platform teamsTrack record of delivering data and AI initiatives with clear business impactStrong understanding of data platforms, analytics, and ML/AI technologiesExperience operating in complex, matrixed organisationsBusiness & Leadership SkillsStrong commercial acumen and ability to link AI initiatives to business valueExcellent stakeholder management and influencing skills at senior levelsAbility to operate strategically while staying close to executionExperience leading cross-functional initiatives end-to-endMindsetPragmatic and delivery-focused, with a bias for actionCurious, innovative and comfortable challenging the status quoStrong communicator, able to translate complex topics into clear business languagePassion for building and developing high-performing teamsBenefits & PerksCompetitive salary (depending on experience) + bonus25 days annual leave plus public holidays. Plus a holiday buy back schemePension schemeHealth and wellness programsSignificant career progression opportunities, with potential to take on a wider role in the futureOpportunity to join a leading brand in a high growth global businessFun culture with company-wide contests and prizesOur Company & PurposeCorpay is a global leader in business payments, laser focused on developing smarter ways for businesses to pay their expenses. Since 2000, Corpay has developed innovative digital solutions that help businesses better track, manage, and pay their expenses. Today, Corpay is an S&P 500 company with hundreds of thousands of customers using our products in over 100 countries. Companies of all sizes, industries and geographies rely on our product portfolio to manage spending more quickly, efficiently and securely than ever before.We embrace a culture grounded in five key values: integrity, collaboration, innovation, execution and people. These values offer you the opportunity to 'thrive & grow' through career development, volunteer, community, and wellness initiatives. This allows you to create a balance between professional goals and personal achievement.Corpay is also committed to building and nurturing a culture of diversity, inclusion, equality, and belonging by:Welcoming people of different backgrounds, cultures, ethnicities, genders, and sexual orientations;Empowering our people to share their experiences and ideas through open forums and individual conversations; andValuing each person's unique perspectives and individual contributions.Embracing diversity enables our people to "make the difference" as CORPAY and its more than 8,000 employees continue to shape the future of global payments. Learn more by visiting or following Corpay on LinkedIn.Equal Opportunity/Affirmative Action EmployerCorpay is an Equal Opportunity Employer. Corpay provides equal employment opportunities to all employees and applicants without regard to race, color, gender (including pregnancy), religion, national origin, ancestry, disability, age, sexual orientation, gender identity or expression, marital status, language, ancestry, genetic information, veteran and/or military status or any other group status protected by federal or local law. If you require reasonable accommodation for the application and/or interview process, please notify a representative of the Human Resources Department.For more information about our commitment to equal employment opportunity and pay transparency, please click the following links: EEO and Pay TransparencyWhy Join Corpay?Impact: Play a pivotal role in a function, bringing your expertiseGlobal Reach: Be part of a company with a presence in over 80 countries and a team of more than 10,000 employees worldwide.Culture: Join a passionate, collaborative, and inclusive team that values your contributions.Rewards: Competitive compensation package, including equity, health benefits, and more.Growth: Opportunities for professional development and career advancement in a fast-growing company.CORPAY Enjoys Global Recognition Including:Forbes Global Growth Champion: CORPAY (FLEETCOR) is one of the 250 fastest-growing companies in the world as determined by Forbes and Statista.Forbes World's Most Innovative Companies: CORPAY (FLEETCOR) has made this prestigious list of leading innovative companies 4 years in a row!Fortune 1000 Company: CORPAY (FLEETCOR) was one of the largest movers in the new rankings of the largest companies in America, ranking .S&P 500: In 2018, CORPAY (FLEETCOR) joined the S&P stock index comprised of the 500 leading US stocks. CorpayCorpay is a global technology organisation that is leading the future of commercial payments with a culture of innovation that drives us to constantly create new and better ways to pay. Our specialized payment solutions help businesses control, simplify, and secure payment for fuel, general payables, toll and lodging expenses. Millions of people in over 80 countries around the world use our solutions for their payments.All offers of employment made by Corpay (and its subsidiary companies) are subject to the successful completion of satisfactory pre-employment vetting by an independent supplier (Experian). This is in accordance with Corpay's Resourcing Policy and include employment referencing, identity, adverse financial, criminal and sanctions list checks. We do this to meet our legal and regulatory requirements.Corpay is dedicated to encouraging a supportive and inclusive culture among our employees. It is within our best interest to promote diversity and eliminate discrimination in the workplace. We seek to ensure that all employees and job applicants are given equal opportunities.Notice to Agency and Search Firm Representatives: Corpay will not accept unsolicited CV's from agencies and/or search firms for this job posting. Resumes submitted to any Corpay employee by a third party agency and/or search firm without a valid written & signed search agreement, will become the sole property of Corpay. No fee will be paid if a candidate is hired for this position as a result of an unsolicited agency or search firm referral. Thank you.

Senior Data Scientist - Technical Specialist Salary: Competitive Plus Benefits Location: London Store Support Centre and Home, London, EC1M 6HA Contract type: Permanent Business area: Data & Analytics Closing date: 22 June 2026 Requisition ID: At Sainsbury's, data sits at the heart of how we operate, innovate and serve our customers. Our Data & Analytics team is building a technically advanced, commercially focused and impactful capability, powering our Next Level Strategy and helping to create a Sainsbury's powered by industry leading AI algorithms. We use data, technology and advanced analytics to drive better decisions across the business, from forecasting and optimisation to experimentation, personalisation and machine learning. With one of the richest retail datasets in the UK and a portfolio spanning Sainsbury's, Argos, Habitat and Nectar, the opportunity to innovate is huge. Here, you'll tackle complex challenges at scale, create measurable impact and grow quickly alongside brilliant colleagues. People who thrive with us combine business understanding, technical expertise and curiosity, with a natural instinct for problem-solving. Join us and help shape the future of retail through data and AI. Senior Data Scientist - Technical Specialist - Hybrid Working - London/Home In Customer Data Science (part of the Data Science Hub), we build the systems behind personalised customer decisioning - from customer segmentations to offer optimisation. We impact millions of customers, bringing them value and earning their loyalty. This team already personalises all of the offers you see in the Nectar app, but now we're growing in ambition and scale. We aim to personalise everything that matters - offers, online recommendations, digital experiences, communications. And we aim to achieve this using our incredible data asset, our rich customer understanding, and state of the art machine learning and AI. This is a new and unique role. You'll operate as a deep technical specialist, floating across two teams in Customer Data Science (and more as we grow). You're not here to manage a team; you're here to solve the hardest problems, raise the technical bar, and ensure that we are building robust, production grade products. This isn't a consultancy role - you'll drop into ambiguous, high impact problems, and solve them yourself. But you'll also define the patterns we need - how we build models, how we productionise them, how we scale without breaking. What you'll do Solve the hard problems Take on ambiguous, high-value problems across customer understanding, personalisation, optimisation and decisioning. Advance techniques used across the team (uplift modelling, optimisation, causal inference, recommendations, real time decisioning). Set us up for success Define and embed best practice across modelling, experimentation, deployment, and model lifecycle management. Drive consistency in how we structure codebases, version control, testing and reproducibility. Coach through doing - pairing on code, demonstrating standards, piloting your ideas. Represent our needs to the Platform team, ensuring we get the ML Ops platform we need. Work with the ML Engineering team to shape how we architect our end to end solution - allowing us to reach more customers more quickly, iterate more rapidly, make our data products more available, and reduce friction and hand offs. Be an enthusiastic member of our community Become the recognised data science technical expert in Customer Data Science, bringing new ideas for future approaches, including state of the art techniques where appropriate. Understand how our business really works, including by supporting our stores during peak trading periods. Actively contribute to our vibrant Data & Analytics community of over 800 colleagues, providing a view on new techniques and approaches that can drive positive change in wider teams. Who you are We're looking for a highly motivated self starter - someone who fixes problems and creates value without micromanagement. You need to thrive in an ambiguous role, and know how to balance our need for technical rigour against our need to deliver commercial and customer value. Deep experience in Data Science roles, with evidence of solving complex problems end to end. A record of building personalisation systems which run in production, and an understanding of the value these generated. Experience working in an Agile way, and ability to understand the trade off between immediate value, future value, and technical rigour. A strong ability to communicate ideas to audiences of varying technical background and seniority. Data Science expertise Strong grounding in statistical modelling and machine learning, such as predictive modelling at scale, unsupervised learning, causal inference, experimentation, optimisation and decisioning Strong understanding of the "how" behind the algorithm; ability to select the right technique for a given objective and avoid pitfalls. Curiosity, scepticism and attention to detail regarding data quality, samples, bias and ethics. Extensive programming ability across Python and strong ability to use SQL, with a proven experience of developing complex solutions in a corporate environment. Solid understanding of version control, dependency management, CI/CD and automated testing, and batch and near real time processing. Practical experience working on cloud based ML Ops platforms. Ability to see the big picture - from data ingestion to decisioning output. Development and coaching A strong awareness and understanding of technology trends and direction in Data Science, analytics and AI. Ability to support in the development, training and mentoring of others. Extensive Data Science background A record of building systems which run in production A strong ability to communicate ideas to audiences of varying technical background and seniority Strong grounding in statistical modelling and machine learning, including predictive modelling and recommendations/decisioning Extensive programming ability across Python and strong ability to use SQL Solid understanding of working with production codebases, such as version control, CI/CD, batch and real time processing Strong understanding of ML Ops and working in cloud environment. We are committed to being a truly inclusive retailer so you'll be welcomed whoever you are and wherever you work. Around here, there's always the chance to try something new - whether that's as part of an evolving team or somewhere else across the business - and we take development seriously and promise to support you. We also recognise and celebrate colleagues when they go the extra mile and, where possible, offer flexible working. When you join our team, we'll also offer you an amazing range of benefits. Here are some of them: Starting off with colleague discount, you'll be able to save 10% on your shopping online and instore at Sainsbury's, Argos, TU and Habitat, and we regularly increase the discount to 15% at points during the year. We've also got you covered for your future with our pensions scheme and life cover. You'll also be able to share in our success as you may be eligible for a performance related bonus of up to 20% of salary, depending on how we perform.Your wellbeing is important to us too. You'll receive an annual holiday allowance, and you can buy up to an additional week's holiday, and we provide private healthcare. We also offer other benefits that will help your money go further such as season ticket loans, interest free car loan of up to £10k, cycle to work scheme, health cash plans, salary advance (where you can access some of your pay before pay day) as well access to a great range of discounts from hundreds of other retailers. And if you ever need it there is also an Employee Assistance Programme.Moments that matter are as important to us as they are to you which is why we give up to 26 weeks' pay for maternity or adoption leave and up to 4 weeks' pay for paternity leave. Please see for a range of our benefits (note, length of service and eligibility criteria may apply).

"The AI company that's revolutionizing Hollywood" Flawless is transforming Hollywood with assistive AI. Our tools empower filmmakers to edit, localize, and refine performances while preserving artistic intent. Designed to support, not replace, artists, our technology expands what is possible on screen and gives creators freedom to tell stories with greater impact and reach audiences in new ways. From enabling seamless multilingual releases to eliminating the need for costly reshoots, Flawless solves critical challenges that slow down productions and limit distribution. We are also setting the standard for ethical AI in entertainment. Our Artistic Rights Treasury (A.R.T.) is a rights management solution that protects artists and rights holders, ensuring that innovation moves forward with transparency and respect for creative ownership. What We're Building Research Services builds the infrastructure that enables scientists to train, evaluate, and deploy models at scale - forming the foundation of Hollywood's AI transformation. Our team sits at the intersection of large-scale data systems, machine learning, and high-performance computing. We own the full stack, from data ingestion and curation through distributed training and production inference, enabling researchers to move quickly while maintaining reliability and scalability. This role focuses on building and optimizing systems for large-scale multimodal datasets, including video, embeddings, and metadata, ensuring they are fast, reliable, and production-ready. The Role We're looking for experienced ML Systems Engineers to join our Research Services team and help build the infrastructure that powers machine learning across Flawless. This role is open across multiple levels, from Senior Engineer through Staff Engineer. The level and scope of responsibility will be determined based on your experience, technical depth, leadership impact, and track record of delivery. As an ML Systems Engineer, you'll work closely with scientists, machine learning engineers, and platform teams to design and build the systems that underpin model development and deployment. You'll contribute hands on across data platforms, training infrastructure, evaluation systems, model lifecycle management, and production inference. More senior candidates will be expected to provide technical leadership, drive architectural decisions, mentor other engineers, and influence infrastructure strategy across multiple initiatives. What You'll Do Data Platforms for Machine Learning Build and evolve data platforms used to curate and manage large scale multimodal datasets. Design systems that index, process, and enrich thousands of videos through machine learning pipelines. Optimize data storage and access patterns for efficient model training and experimentation. Improve reliability, scalability, and observability across the data ecosystem. ML Training Infrastructure Build and optimize infrastructure for large-scale model training. Improve performance across single-node and distributed training environments. Scale data loading, preprocessing, and training workflows. Ensure training pipelines are reproducible, efficient, and easy to operate. Evaluation & Experimentation Systems Develop systems for collecting, storing, and analyzing model outputs. Build tooling for dataset exploration, experiment tracking, and model comparison. Enable scientists to iterate rapidly while maintaining robust evaluation practices. Model Lifecycle Management Design and maintain infrastructure for model versioning, experimentation, validation, and deployment. Improve reproducibility and governance across the machine learning lifecycle. Support the promotion of models from research through production. Production Inference Systems Build and optimize inference infrastructure for production workloads. Define and improve model serving protocols and deployment patterns. Enhance performance, reliability, and scalability of production inference systems. What We're Looking For We're interested in engineers who enjoy building systems that make machine learning teams more effective and productive. We're particularly interested in candidates with: Experience building machine learning infrastructure, ML platforms, data platforms, or large-scale backend systems. Strong Python engineering skills and experience building production services. Deep understanding of data pipelines and performance trade offs across storage, networking, memory, and compute. Hands on experience working with machine-learning frameworks such as PyTorch. Experience building and operating distributed systems. Experience working with large-scale datasets and high throughput data processing pipelines. Familiarity with modern data storage and analytics technologies, including columnar data formats and data lake architectures. Strong debugging, problem-solving, and systems design skills. Experience collaborating effectively with cross functional teams. Additional Expectations for Staff Engineers Demonstrated technical leadership across significant infrastructure initiatives. Experience defining architecture and technical strategy for complex systems. Ability to influence engineering direction beyond an individual team. Track record of mentoring engineers and raising technical standards. Experience balancing immediate research needs with long-term platform investments. Nice to Have Experience working with video, media, or multimodal machine learning pipelines. Familiarity with embeddings, vector search, or retrieval systems. Experience operating production inference systems. Frontend experience (React or similar) for building internal tools and workflows. Why work at Flawless? You will be working in an environment based on trust, autonomy and collaboration, and this is a great opportunity for someone who wants to be part of a growing company in its most exciting stage of development. You can play a part in shaping the future of a company that's caring, creative and collaborative. In addition to this, you'll also receive: - Autonomy - A hybrid working environment - Competitive Salary - All permanent employees receive generous stock options I don't meet all the listed requirements-should I still apply? Absolutely! Research shows that women and underrepresented groups often hesitate to apply unless they meet every qualification, but at Flawless, we actively work to break down those barriers. We believe diverse perspectives, experiences, and backgrounds make us stronger, and we are committed to supporting and elevating underrepresented talent. If you're excited about the role, share our values, and believe you can contribute meaningfully, we encourage you to apply-even if you don't meet every single requirement. Your unique skills and perspective matter, and we'd love to hear from you

Location London, Melbourne, Sydney Employment Type Full time Location Type Hybrid Department Engineering Who are Heidi? Heidi is building an AI Care Partner that supports clinicians every step of the way, from documentation to delivery of care. We exist to double healthcare's capacity while keeping care deeply human. In 18 months, Heidi has returned more than 18 million hours to clinicians and supported over 73 million patient visits. Today, more than two million patient visits each week are powered by Heidi across 116 countries and over 110 languages. Founded by clinicians, Heidi brings together clinicians, engineers, designers, scientists, creatives, and mathematicians, working with a shared purpose: to strengthen the human connection at the heart of healthcare. Backed by nearly $100 million in total funding, Heidi is expanding across the USA, UK, Canada, and Europe, partnering with major health systems including the NHS, Beth Israel Lahey Health, MaineGeneral, and Monash Health, among others. We move quickly where it matters and stay grounded in what's proven, shaping healthcare's next era. Ready for the challenge? The Role Working closely with the Product Lead, you will be a Mid-level or Senior Fullstack Engineer who operates at the intersection of core product development and clinical application. This role requires formal medical training and real clinical experience. Your clinical background will directly inform how we design, evaluate, and ship AI features that support real-world care delivery. Experience working on clinical AI products is highly valued, as you'll be shaping systems that must perform safely in production environments. What you'll do: Build end-to-end AI features: Architect and ship fullstack solutions (from React frontends to Python backend services) that leverage our voice AI and LLMs to automate clinical workflows. Operationalize Voice AI: Implement and fine-tune audio processing pipelines, ensuring our Automatic Speech Recognition (ASR) and LLM agents perform accurately in diverse, real-world medical environments. Bridge the gap between model and product: Translate complex feedback from clinicians into technical solutions, rapidly prototyping and deploying improvements to model behavior, prompting strategies, and audio handling. Optimise for real-time interaction: Tune fullstack performance to handle real-time audio streaming and token generation, minimizing latency so clinicians have a seamless conversational experience. Partner with implementation and clinical teams: Shorten the feedback loop by shipping critical integrations and feature requests from concept to production in days, not quarters. What we will look for: Mastery of Fullstack fundamentals: You are equally proficient in Python and modern frontend frameworks (React/TypeScript), capable of owning a feature from the database schema to the UI interaction. Applied AI & Voice fluency: You have a working knowledge of LLM integration (RAG, prompt engineering) and audio technologies (ASR, speech processing) and know how to build around their probabilistic nature. Pragmatic problem solving: You balance engineering purity with the need for speed; you know when to build a robust system and when to ship a tactical solution to unblock a customer. Cloud fluency (AWS or GCP): You can spin up your own infrastructure (containers, serverless functions) and manage CI/CD pipelines to get your code into the hands of users independently. Rigorous testing in production: You understand that "works on my machine" isn't enough; you implement observability and feedback loops to monitor how your AI features perform in the wild. Medical degree with clinical experience, and ideally experience working on clinical AI products What do we believe in? Heidi builds for the future of healthcare, not just the next quarter, and our goals are ambitious because the world's health demands it. We believe in progress built through precision, pace, and ownership. Live Forever - Every release moves care forward: measured, safe, and built to last. Data guides us, but patients define the truth that matters. Practice Ownership - Decisions follow logic and proof, not hierarchy. Exceptional care demands exceptional standards in our work, our thinking, and our character. Small Cuts Heal Faster - Stability earns trust, speed delivers impact. Progress is about learning fast without breaking what people depend on. Make others better - Feedback is direct, kindness is constant, and excellence lifts everyone. Our success is measured by collective growth, not individual output. Our mission is clear: expand the world's capacity to care, and do it without losing the humanity that makes care worth delivering. Why you should Join Heidi Real product momentum. We're not trying to generate interest, we're channeling it. This is a rare chance to create a global impact as you immerse yourself in Australia's fastest growing start-up. Equity from day one. When Heidi wins, you win. You'll share directly in the success you help create. Unmatched impact. Play a pivotal role at a critical growth moment - all while working on a product that delivers tangible value to clinicians and patients every day. Work alongside world-class talent. Join a team of operators and builders who've scaled unicorns. Global reach. Help shape our international expansion as we bring Heidi to key international markets. Growth and balance. Enjoy a personal development budget, dedicated wellness days, subsidised gym membership, and your birthday off to recharge. Flexibility that works. A hybrid environment, with 3 days in the office. Heidi's commitment to Diversity, Equity and Inclusion Heidi is dedicated to creating an equitable, inclusive, and supportive work environment that brings people together from diverse backgrounds, experiences, and perspectives. Our strength is in our differences. We're proud to be an equal opportunity employer and are proud to welcome all applicants as we're committed to promoting a culture of opportunity for all. Help us reimagine primary care and change the face of healthcare in Australia and then around the world.

Senior Engineering Manager - Machine Learning United Kingdom We are on a mission to pioneer the world's next era of play. As we grow across Europe and Latin America, we're building The Playstack - the technology powering the next generation of sports, gaming, and fan experiences. Join us, and help make it the most widely used platform in the world! From operations, to marketing, to product, we are looking for talented people who will shape how millions of customers play, watch, and connect every day. About the role We're looking for a hands on and motivated Senior Engineering Manager for Applied Machine Learning & Research to support the development and delivery of machine learning systems at Super Technologies. By combining cutting edge applied machine learning, foundational research, and seamless ML operations, the team harnesses data to revolutionize the online gambling and sports betting experience. From predictive analytics and personalization to fraud detection and real time recommendations, the team transforms complex data into actionable insights that enhance customer engagement, trust, and satisfaction. By leveraging machine learning to create smarter systems and deeper customer understanding, the team plays a pivotal role in shaping the future of the company, fostering a data driven culture, and ensuring we deliver unparalleled experiences to our players. In this role, you'll split your time between technical contribution, project coordination, and people management - helping your team succeed while staying close to the code. We're looking for someone who has: Master's or Ph.D. in Computer Science, Data Science, Machine Learning, or a related field Proven experience (4+ years) in machine learning and data science roles Proven experience (5+ years) leading/managing engineering teams, supporting the growth and performance of engineers Strong programming skills in Python and experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Experience with cloud computing platforms primarily AWS and containerisation technologies (e.g., Docker, Kubernetes) Excellent problem solving skills and the ability to work independently and collaboratively Strong communication and interpersonal skills Preferred qualifications: Experience in the gaming or entertainment industry Experience working with tools and technologies such as Spark, Snowflake, Qwak, MLFlow, Airflow, etc Contributions to open source AI/ML projects or participation in AI/ML competitions (e.g., Kaggle) Experience with training and fine tuning large scale foundation models (e.g., GPT, BERT, T5) for various tasks Publications in top AI conferences, such as AAAI, IJCAI, NeurIPS, ICML, ICLR What you'll be doing: Technical Expertise: Design, develop, and deploy advanced machine learning models to solve complex business problems Stay updated with the latest trends and advancements in machine learning and AI technologies Conduct code reviews and ensure best practices in model development and deployment Project Management: Manage and prioritise machine learning projects to align with business goals and objectives Ensure timely delivery of high quality machine learning solutions Coordinate with cross functional teams to integrate machine learning models into production systems People Management: Lead and mentor a team of 4-5 talented data scientists and ML engineers, providing guidance and support in their day to day activities Oversee the execution, development, growth and performance of the ML team Foster a collaborative and innovative team environment while building strong partnerships with product management and stakeholders About Super We are a global technology group, dedicated to building the future of entertainment and fan centric experiences. With commercial markets in Brazil, Belgium, Poland, Romania, Greece and Serbia, and a network of offices across Spain, Croatia, Malta, Gibraltar, the Netherlands and the UK, we are a truly international organization. Our purpose at Super has evolved from sports and betting into creating the platform that stretches into the wider world of technology driven entertainment. With a growing and diverse team of more than 5,000 people, we create immersive, responsible, and personalised experiences for millions of customers worldwide. Shaping the Future of Play Everything we do at Super is rooted in doing what is right: for customers, for each other, and for our long term vision. Our Culture Manifesto is our North Star. It captures our purpose, mission, and the six core beliefs that shape how we think, make decisions, and act every day. Want to explore our culture in more detail? Visit our careers page:super.xyz/careers Super is committed to the highest standards of compliance, safety, and responsibility. As such, we are active members of the International Betting Integrity Association (IBIA) and the European Gaming & Betting Association (EGBA). At Super, we operate as a high performing team. We hire and grow talent based on ability and potential, regardless of background and identity because we know diverse perspectives, drive better performance.

Why Join Us? To shape the future of travel, people must come first. Guided by our Values and Leadership Agreements, we foster an open culture where everyone belongs, differences are celebrated and know that when one of us wins, we all win. Benefits We provide a full benefits package, including exciting travel perks, generous time off, parental leave, a flexible work model (with some pretty cool offices), and career development resources, all to fuel our employees' passion for travel and ensure a rewarding career journey. We're building a more open world. Introduction to the team The Unified Personalization Service team is part of Expedia Product & Technology. UPS is building Expedia Group's centralized, real time personalization engine across brands and channels, powering ranking, recommendations, retrieval, and other adaptive experiences that help travelers see more relevant, contextual, and useful experiences throughout their journey. Role Overview We are looking for a Machine Learning Scientist III to help build production ML systems for personalization, with emphasis on deep learning, neural recommender systems, sequential and session based modeling, embeddings, scalable experimentation, and reliable model deployment. In this role, you will Develop, apply, and advance machine learning solutions for personalization use cases, translating business and customer problems into scalable scientific approaches and production ready models. Design experiments, evaluate model performance, and use data driven methods to improve relevance, ranking, recommendation, and overall customer experience across personalization systems. Partner across engineering, product, analytics, and science teams to define solution approaches, influence technical direction, and deliver ML capabilities that can operate across multiple products and domains. Contribute technical depth in model development, feature design, data preparation, offline and online evaluation, and the operationalization of machine learning solutions in production environments. Apply strong technical judgment to system design, API design, data modeling, and low level solution design that support robust, maintainable, and extensible ML powered services. Safely integrate and operate AI/ML enabled solutions that improve outcomes, including familiarity with AI driven systems, tools, or workflows and applying AI/ML concepts to real world products. Minimum Qualifications Bachelor's degree in Computer Science, Machine Learning, Statistics, Mathematics, a related technical field, or equivalent professional experience. 5+ years of relevant experience in machine learning, applied science, data science, or software development, including delivering production grade ML solutions. Demonstrated ownership of machine learning solutions within a service, multi service, or domain level scope, with accountability for model quality, experimentation, and operational performance. Strong foundation in machine learning methods, statistical analysis, experimentation, feature engineering, and working with large scale datasets in production environments. Proficiency in software engineering practices for scientific systems, including coding, low level design, API design, data modeling, and collaboration with engineering teams to productionize solutions. Preferred Qualifications Advanced degree in Machine Learning, Computer Science, Statistics, Mathematics, or a related technical field. Experience building and scaling personalization, recommendation, ranking, retrieval, or relevance models in large, complex consumer facing environments. Experience with neural recommendation systems, sequential or session based recommendation, transformer based recommenders, semantic retrieval, or representation learning at scale. Experience with foundation models, LLMs, embedding models, semantic IDs, hybrid LLM recommender systems, or retrieval augmented personalization workflows. Demonstrated ability to use data, metrics, and experimentation to guide prioritization and decision making while balancing scientific rigor, product impact, and platform scalability. Experience with production ML workflows such as model serving, experimentation frameworks, feature or data pipelines, monitoring, model lifecycle management, or MLOps. Accommodation Request If you need assistance with any part of the application or recruiting process due to a disability, or other physical or mental health conditions, please reach out to our Recruiting Accommodations Team. Equal Opportunity Employer Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, gender, sexual orientation, national origin, disability or age.