233 jobs found

User Researcher (CGI) Shape evidence led digital services that improve outcomes for users, organisations, and communities. Work within multidisciplinary teams (design, product, technology) to uncover user needs, influence decision making, and support the delivery of inclusive and impactful digital services. Conduct user research studies and interpret findings. Translate insights into design recommendations. Collaborate with stakeholders to inform product strategy. Service Designer (CGI) Help design user centred services that solve real world challenges and deliver meaningful outcomes for citizens and organisations. Co create intuitive and accessible service designs. Facilitate design workshops with multidisciplinary teams. Advise on user experience and accessibility standards. Senior Service Designer (CGI) Play a key role in shaping user centred, end to end services that meet real world needs and deliver measurable value. Lead service design initiatives and influence organisational change. Mentor less experienced designers. Drive innovative solutions across the service lifecycle. Interaction Designer (CGI) Design intuitive, accessible, and user centred government services that improve how people interact with critical public sector systems. Transform research insights into high fidelity digital experiences. Ensure compliance with government accessibility best practices. Advise on interaction design strategy. Solutions Architect Designer (Telecoms Company) Design and implement systems architecture that meets business needs and incorporates emerging technologies. Develop functional specifications and architecture models. Lead multi platform solution delivery. Maintain Enterprise Architecture documentation. Data Scientist - Energy (Telecoms Company) Drive development and delivery of solutions that strengthen electricity network performance and resilience. Collaborate with Distribution Network Operators to identify operational challenges. Build models and algorithms to support decision making. Engage with universities and research partners. Technical Architect (LA International) Design and produce architectural artefacts for end to end solutions, supporting delivery and implementation. Create high level to detailed solution architecture. Guide product groups in architecture governance. Review and assure quality of artefacts delivered by suppliers. Linux Systems Administrator (Rise Technical Recruitment) Maintain, automate, and optimise Linux based systems underpinning a cloud hosted SaaS platform. Administer Ubuntu and Debian environments. On call incident response and system optimisation. Automate provisioning and deployments using Ansible.

Job Title Technical Product Owner (AI/ML Platform) Location London Corporate Title Vice President Overview As the Technical Product Owner for the AI/ML Platform, you will own the vision, roadmap, and delivery of the core engineering and MLOps capabilities that empower our data scientists and developers. You will be the crucial link between the advanced needs of our AI/ML practitioners and the platform engineering teams that build the foundational tools. This role requires a deep technical understanding of the machine learning lifecycle and the ability to translate architectural and data science requirements into a clear, actionable product backlog. Your primary objective is to maximize the velocity, efficiency, and scalability of how AI/ML models are built, deployed, and managed in Credit Risk. What we'll offer you Hybrid working - we understand employee expectations and preferences are shifting. Competitive salary and non-contributory pension. 30 days holiday plus bank holidays, with option to purchase additional days. Life assurance and private healthcare for you and your family. Flexible benefits including retail discounts, Bike4Work scheme and gym benefits. Opportunity to support a wide ranging CSR programme and 2 days volunteering leave per year. Key Responsibilities Define and communicate a clear product vision and roadmap for the AI/ML platform, focusing on technical capabilities such as data pipelines, feature stores, model serving infrastructure, and monitoring frameworks. Create, maintain, and prioritise the product backlog with focus on platform features, architectural enhancements, and developer tooling. Translate complex technical requirements from data scientists and engineers into well defined epics, user stories, and API contracts. Act as the primary technical interface for the platform's users (data scientists, ML engineers, application developers). Partner closely with tech leads and architects to make key design decisions, ensuring scalability, robustness and alignment with enterprise technology standards. Make decisive priority calls balancing new data science capabilities, technical debt reduction, system performance improvement and strategic business initiatives. Own release of new platform features, APIs, and tools. Drive adoption by creating documentation, running demos, and providing support for technical practitioners. Skills & Experience Proven experience as a Technical Product Owner, Platform Product Manager, or senior engineering/architecture role with strong product instincts. Deep technical understanding of the end to end AI/ML lifecycle and associated engineering challenges (MLOps, CI/CD for models, data engineering). Experience working directly with cloud platforms (GCP, AWS, Azure) and containerisation technologies (Docker, Kubernetes). Strong background in software engineering, comfortable discussing APIs, microservices architecture, data schemas, and infrastructure. Proven ability to work in an Agile environment with engineering teams to define and deliver technical products. Excellent communication skills, with ability to articulate complex technical trade offs and decisions to both technical and non technical stakeholders. How we'll support you Training and development to help you excel in your career. A culture of continuous learning to aid progression. A range of flexible benefits you can tailor to suit your needs. Equal Opportunities We welcome applications from all people and promote a positive, fair and inclusive work environment. We value diversity and, as an equal opportunity employer, we make reasonable adjustments for those with a disability (e.g., screen readers, assistive hearing devices, adapted keyboards). If you have a disability, health condition or require adjustments during the application process, please contact our Adjustments Concierge by email.

Project description We are hiring in the Middle East. There are many projects and opportunities in the region. Our team consists of frontend and backend developers, data analysts and data scientists, architects, analysts and project managers. Responsibilities Develop and maintain scalable solutions using Python, PySpark, and SQL. Design and implement data pipelines (ingestion, transformation, modelling, data quality checks, automation). Build and integrate APIs (REST, SOAP, gRPC), including authentication and authorization. Contribute to application architecture design, applying best practices and design patterns. Implement Test-Driven Development (TDD) and ensure high code quality. Support and enhance CI/CD pipelines and DevOps processes. Work with cloud platforms (AWS, Azure) and data platforms such as Databricks and Palantir Foundry. Develop UI components and dashboards using Dash, JavaScript, and React. Integrate with market data and investment platforms. Support quantitative models and analytics (Monte Carlo simulations, pricing, risk, factor modelling). Contribute to portfolio management processes (asset allocation, rebalancing, attribution). Analyze complex datasets and deliver actionable insights for business and investment decisions. Gather and challenge business requirements, define solutions, and report on delivery progress. Collaborate within Agile teams, ensuring effective communication and alignment. Stay updated on emerging technologies and industry trends, proposing improvements. Balance short-term deliverables with long-term architectural goals. Skills Must have: Python (Advanced), PySpark (Medium), SQL (Advanced) Dash (Python framework), JavaScript (Medium), React (Preferred), OpenFin / FTC3 (Preferred) Azure (Preferred), AWS (Medium) DataBricks (Preferred), Palantir Foundry (Medium) Test-driven Development (Advanced), CICD (Medium), DevOps (Advanced) Application Architecture design and development (Design patterns etc) Data Engineering (Ingestion, Curation, Modelling, Automation, Data Quality Checks) (Preferred) APIs (patterns, authorization, SOAP, REST, GRPC) (Advanced) Data Science (Preferred) Understand and provide insights on emerging industry trends. Domain Knowledge Knowledge / experience in financial markets and alternative asset classes (Hedge Funds) Knowledge / experience in end-to-end portfolio management (asset allocation, portfolio construction, rebalancing, implementation, attribution) Experience with sourcing data from, and integrating with, core investment and/or market data platforms Knowledge / experience with Quant processes (Monte Carlo simulation, pricing engines, optimization techniques, factor modelling, risk) Nice to have Ability to gather requirements, challenge, define structure and report upon status of deliverables. Strong collaboration and team culture, working in Agile delivery. Strong problem-solving skills and ability to effectively resolve issues in a timely manner. Excellent interpersonal skills, including collaboration, facilitation, and negotiation. Excellent written and verbal communication skills. Ability to balance the long-term ("big picture") and short-term implications of individual decisions. Other Languages: English: C1 Advanced Seniority: Senior Location: London, United Kingdom of Great Britain and Northern Ireland

The opportunity Substrate is building a network of fully autonomous wet labs, cloud-based data production facilities for AI biology, integrated with foundation models to become the critical infrastructure layer for AI-driven biological discovery. Our first node opens in King's Cross, London, with several integrated workcells and two scientific verticals online by mid 2027. Our customers range from foundation model labs to global pharma. We are hiring a founding software engineer to lead the team that builds Substrate's operational software, the system that turns scientific intent into executed lab work, captures every run as structured data, and routes that data back to model training, customer pipelines, and Substrate's own data factory. This is a player coach role. You will write the first production code for the orchestrator, the customer interface, and the resource management layer, and you will recruit and lead the engineers who come after. About Substrate Substrate is spinning out of Automata, the UK lab automation company that has built the workcell platform our labs run on. Our four co founders are Mostafa ElSayed (CEO and founder of Automata), Oli Hoy (formerly VP Customer Experience at Automata), Alexey Morgunov (AI Scientist co founder, leading the Intelligence Software product), and a Founding Biology Lead joining shortly. We are aiming to have ramped up to 32 people by the end of Q1 2027. We are funded in parallel by a combination of venture funding and government grants. We are not a cloud lab, and we are not a CRO. We are an autonomous lab platform with closed loop integration available as one operating mode for foundation model partners. The role You will own the operational software product end to end. The product has five surfaces. The loop orchestrator is the heart of it: two agentic translation layers that convert scientific intent (model output, natural language, or structured input) into executable, automated workflows, and convert workflow outputs and run metadata back into destination specific formats for delivery to foundation models, LIMS, customer data lakes, and ELNs. Resource management will track consumables, reagents, and labware, and maintain a live representation of the physical lab so that physical inputs can be mapped onto workflow outputs. The customer interface is API first with a web front end. The workflow orchestrator sits above Automata's LINQ scheduler and manages capacity allocation across customers, verticals, and device groups. The pricing and forecast engine calculates predicted and actual platform inputs and translates them into customer cost. You will write the first production code, set the architecture, set the engineering culture, and grow the team. You will have the opportunity to build a team and help set the culture within the company. You will work closely with Alexey on the boundary between our operational software and our intelligence software (the AI Scientist and AI Assays products), and with the founding biology team on the orchestrator behaviour on the lab side. What you will do in your first twelve months PHASE 0: NOW TO AUG 2026 Land in the team. Lock the architecture for the orchestrator and the customer interface. Decide the build vs buy boundary against LINQ. Ship the first end to end thin slice: a simple workflow submitted via the customer API, executable on a workcell, with run metadata captured and returned. Set the engineering culture: code review, deployment, on call, observability. Pick the languages, frameworks, and tooling we will live with. PHASE 1: SEP TO DEC 2026 Stand up the resource management and digital twin services. Wire them into the protein engineering workflows being onboarded by the founding biology team. Hire the first software engineer alongside you. Define the role, run the process, close the offer. Ship the first version of the pricing and forecast engine. Connect it to the customer interface so that customers see predicted cost before they submit. PHASE 2: JAN TO MAR 2027 Ramp up hiring. Move from solo building to leading a larger team. Bring the workflow orchestrator above LINQ into production. Manage capacity allocation across the protein engineering vertical and the early functional genomics work. Harden the loop orchestrator for the closed loop foundation model partners coming online from mid 2027. Who you are You are an experienced software engineer who has shipped production systems at depth. You have led a small team or are ready to. You write good code at speed, you have strong opinions about architecture, and you have learned (often the hard way) when to defer those opinions. You have worked at the boundary where software meets physical reality (lab automation, robotics, manufacturing, logistics, scientific instruments, energy) and you understand that the interesting failure modes live there. You are excited by the prospect of writing the first lines of code for a system that will run a real lab. You are pragmatic about agentic systems and foundation models; you have used them in production rather than read about them in posts. You want a player coach role specifically. You enjoy interviewing, hiring, mentoring, and building culture, and you do not want to be only an individual contributor or only a manager. You care deeply about building a world class team. You are comfortable with early stage ambiguity, with making decisions on partial information, and with revisiting them when better information arrives. MUST HAVE Five or more years of professional software engineering experience, with at least one leading or co leading a small team. Production experience with backend systems, distributed services, and either workflow orchestration or scheduling systems. Strong working comfort with at least Python, and willingness to learn the necessary tools. Track record of designing APIs that other engineers have actually used. Direct experience of the software to hardware boundary, in lab automation, robotics, manufacturing, or an analogous domain. NICE TO HAVE Experience of an early stage founding engineer role at a venture backed company. Familiarity with foundation model APIs, agentic patterns, and the practical realities of putting them in production. Background in or near scientific computing, bioinformatics, or LIMS / ELN systems. Why this is unusual Most software engineering roles at venture backed companies are either a pure software product or a thin software layer on top of someone else's infrastructure. This is neither. You will be writing the software that decides what physical experiments run, when, on which workcell, with which reagents, for which customer, and you will be doing that inside a wet lab business with biology and engineering colleagues at the same table. Operational software is also one of three product surfaces being built simultaneously. Alexey is leading the efforts on intelligence software (the AI Scientist and AI Assays products). The biology team is building the assay portfolio. Your work has to integrate cleanly with both, and you will spend real time at the boundary. Some engineers find this energising; some find it distracting. Worth knowing in advance which one you are. Compensation and equity We pay competitively against the London market for senior software engineers at venture backed companies, calibrated to seniority and to the specific scope of this role. We will discuss numbers with serious candidates after first conversations. Equity is meaningful, with vesting on the standard four year schedule and a one year cliff. We can talk through the philosophy and the maths in detail when we meet. How we work Working pattern is open. We will design around the strongest candidate, with a bias towards willingness to spend some in person time at our King's Cross site, particularly during the early phases while the team is forming and the architecture is being set. Most of the founding team are in the office most days. 30 days annual leave. A learning budget you can use for conferences, courses, books, and time. The founding team operates on a weekly cadence with a Monday planning meeting and a Friday close, and a quarterly off site. We are direct with each other, we write things down, and we expect to be challenged. The team you will join You will report to Oli Hoy, co founder, who leads our autonomous lab build out and is also responsible for the broader operations of the company. You will work most closely with Alexey Morgunov on the intelligence software boundary, and with the founding biology team on the orchestrator behaviour at the lab side. How to apply Apply via Ashby with whatever you think shows your work best: a CV, a short email, links to GitHub or to systems you have built, a piece of writing you are proud of. We read everything that comes in. Our process is four stages. An initial conversation with Oli to understand what you want from the role and what we want from it. Two technical sessions with our external technical advisor: an architecture deep dive on how you would build the operational software, and a session on how you would build and lead the engineering team. Finally, an in person founder team session covering scope, terms, and any final questions. We aim to move fast on candidates we are excited about; expect roughly two to three weeks end to end. If you are not sure whether you are a fit, send a note anyway. The most useful conversations we have had so far have been with people who were not sure. . click apply for full job details

Wise is a global technology company, building the best way to move and manage the world's money. Min fees. Max ease. Full speed. Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their lives easier and save them money. As part of our team, you will be helping us create an entirely new network for the world's money. For everyone, everywhere. Job Description About the role For our customers, Wise should feel as simple as sending money from A to B. Behind that simplicity is a complex engine of currencies, routes, products, and features, generating terabytes of data every day. Data Products & Insights helps Wise turn that data into products, insights, and decisions at scale. Within this area, the Machine Learning Platform (MLP) team builds and maintains the infrastructure that enables data scientists across Wise to develop, deploy, serve, and monitor machine learning models at scale. Our platform powers predictions and decisions across the business - from fraud detection to treasury management to product personalisation - directly impacting how Wise serves millions of customers worldwide. Your mission and role will be building and maintaining a cost efficient and scalable machine learning platform, that is a delight to use and that provides a good engineering and data science experience while shortening the full experimentation feedback loop - a data scientist does not just deploy models fast, but learns fast which model is better. Your input will directly affect how Wise is making decisions and predictions on billions of events. We are looking for a Senior Software Engineer to join our team in London and help us evolve from a collection of tools into a coherent, self service platform. How we work: We are a small, collaborative team that values product thinking, shared ownership, and continuous improvement. We are in the early stages of introducing structured agile practices and treat every process change as an experiment. The MLP team is part of the Data Products & Insights Squad. We own the infrastructure layer that sits between data scientists and production: model serving, training pipelines, model registry and experiment tracking, feature management, and model monitoring on the line. Our customers are internal - Data Scientists and ML engineers across Wise - and our success is measured by how effectively they can build, deploy, and iterate on models without friction. What will you be working on? Building and maintaining core ML platform services including model serving infrastructure, training pipelines, and experiment tracking Contributing to the evolution of our platform from individual service offerings towards a coherent, user driven product Improving platform scalability, reliability, and operability, ensuring our infrastructure can support hundreds of models in production while making pragmatic trade offs around cost, complexity, and user needs. Improving observability and monitoring across the model lifecycle, helping data scientists understand model health and performance Collaborating with data scientists to understand their workflows, pain points, and needs - treating them as your customers Participating in on call/support rotation, contributing to platform stability and identifying opportunities to reduce operational toil Helping shape the technical and product roadmap by contributing to discovery, spikes (exploratory/investigative work), and architectural decisions Sharing knowledge across the team, reduce silos, mentor others, and help raise engineering standards through design reviews, code reviews, documentation, and continuous improvement. What does it take? You care about bringing value and satisfaction to your customers - the developer/user experience of the people who use your platform matters as much as the technical elegance of the solution You think in systems, not just features - you consider how components interact, where complexity lives, and how to reduce it You are comfortable working across the stack - from infrastructure and orchestration to APIs and developer tooling You take ownership of problems end to end, from understanding the need through to production and beyond You communicate clearly, build consensus, and enjoy collaborating with people from different disciplines - data scientists, product managers, and fellow engineers You have a growth mindset - curious, experimental, and open to giving and receiving regular feedback You share your ideas, continuously improve yourself and the team around you, and are comfortable working collaboratively in a hybrid environment What do you need? We are fully aware that it is uncommon for a candidate to have all skills required and we fully support everyone in learning new skills with us. We value potential and enthusiasm as much as existing expertise. So if you have some of those listed below and are eager to learn more we do want to hear from you! Strong engineering background in Python with experience building and maintaining production systems Experience with Kubernetes - deploying, managing, and troubleshooting containerised workloads Familiarity with ML platform tooling such as MLflow, Airflow, or similar orchestration and experiment tracking frameworks Experience with cloud infrastructure (AWS or GCP) including compute, storage, and networking Understanding of distributed systems principles - you know the trade offs between different architectures and can make pragmatic decisions Experience with observability and monitoring - building dashboards, alerts, and tooling that helps teams understand system health Solid understanding of software engineering best practices - testing, code review, CI/CD, and clean, maintainable code Ability to use AI assisted development tools responsibly, while validating outputs and retaining ownership of code quality. Nice to haves Experience building or contributing to internal developer platforms or self service tooling Familiarity with ML workflows - training, serving, feature engineering, model monitoring (you don't need to be a data scientist, but understanding the domain helps) Experience with Infrastructure as Code (Terraform, CDK, or similar) Exposure to streaming or batch data processing frameworks (Spark, Flink, Kafka) Interest in platform as product thinking - treating adoption, user experience, and feedback loops as first class concerns What you get back The opportunity to shape a platform that directly enables ML driven decisions across a global financial product serving millions of customers A team that values autonomy, experimentation, and continuous improvement - where your ideas about how we work matter as much as what we build Real ownership of the systems you work on - from architecture decisions to production operations Exposure to complex, real world ML infrastructure challenges at scale A collaborative environment where people are grounded, driven, and genuinely enjoy working with others What do we offer Starting salary: £87,500 - £111,000 + RSUs Wise Benefits Our Engineering career map Wise Engineering - Additional Information For everyone, everywhere. We're people building money without borders - without judgement or prejudice, too. We believe teams are strongest when they are diverse, equitable and inclusive. We're proud to have a truly international team, and we celebrate our differences. Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers. If you want to find out more about what it's like to work at Wise visit Wise.Jobs. Keep up to date with life at Wise by following us on Instagram

Description Join us at Amazon as we reinvent shopping and search again! We're not just talking about improving the existing Amazon shopping experiences, we're building a brand-new world where shopping is effortless and intuitive through the power of generative AI. Leveraging state-of-the-art Large Language Models and generative AI, we're creating a live, two-way natural language conversational shopping and search experiences that are fast, helpful and trustworthy. As people turn to Amazon for deeper insights and understanding about products earlier and earlier in their shopping journeys, we're stepping up to the challenge by synthesizing complex information and multiple perspectives so customers can explore Amazon's vast catalog to find exactly the products that solve their particular needs. Imagine having a back and forth conversation with an AI assistant helping you to articulate a problem you're trying to solve, effortlessly answering your product questions and giving you trustworthy advice and recommendations for what to buy. Also imagine a world where this same AI assistant reduces your mental load by proactively predicting and then fulfilling your shopping needs without you needing to interfere, thus saving you time and money along the way. We are building such an AI assistant to become the digital manifestation of the helpful salesperson that asks customers what they need, helps them navigate the store, waits unobtrusively while they look over the shelves, and helps them find complementary goods. What does economics have to teach this salesperson? Can we embed lessons from the behavioral literature to help customers? This is an opportunity to embed economic expertise into large scale generative models. This is just the beginning, and the future is yours to shape. We're searching for pioneers who are passionate about using technology and innovation to fundamentally change how customers shop, and who are ready to make a lasting impact on the industry and even disrupt how Amazon serves customers. You'll be a senior technical leader working with talented scientists, economists, engineers, and product leaders to innovate on behalf of our customers and help turn generative AI shopping into Amazon's next business pillar. Basic Qualifications Experience managing a team of high calibre Software Engineers developing complex, world class, scalable software systems that have been successfully delivered to customers Experience designing or architecting (design patterns, reliability and scaling) of new and existing systems Experience in leading the definition and development of multi tier web services Knowledge of engineering practices and patterns for the full software/hardware/networks development life cycle, including coding standards, code reviews, source control management, build processes, testing, certification, and livesite operations Experience partnering with product and program management teams Preferred Qualifications Experience in communicating with users, other technical teams, and senior leadership to collect requirements, describe software product features, technical designs, and product strategy Experience in recruiting, hiring, mentoring/coaching and managing teams of Software Engineers to improve their skills, and make them more effective, product software engineers Experience delivering products against plan in a fast-paced, multi-disciplined, distributed-responsibility and often ambiguous environment Experience developing, deploying and managing AI products at scale Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice () to know more about how we collect, use and transfer the personal data of our candidates. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

Hey! We're Plum, your smart saving and investing app on a mission to help grow money for life. Whether you're stashing the cash for tea and toast in your first home or catching some rays during retirement, Plum's got your back. Since 2016, over 2 million people in 10 European markets have set aside more than £2 billion with our clever automation and AI -that's the magic of Plum! As recognition for our work, we've received awards from the likes of Deloitte, Finder, and more. That's all down to our passionate team of 200+ Plumsters, who work around Europe to help us achieve our mission. And now we're looking for more brilliant people to join us on our journey. The Role At Plum we're looking for engineers who are passionate about both technology and bringing the best product to our customers. To achieve this mission, we need technical leaders who can look beyond individual features to drive the technical strategy that accelerates our user growth and engagement. We are looking for a Staff Engineer for our First & Last Mile group, the team responsible for driving the core user lifecycle, including user Onboarding, Offboarding, Authentication, Engagement, and Subscriptions. We need a technical leader who understands how to bridge the gap between complex backend services, mobile client architecture, and business impact. You will not only have a strong technical background but also the ability to define technical roadmaps, elevate the engineering culture, and architect systems that enable rapid experimentation across our entire stack. What You Will Do Architect and design modular, scalable, and observable systems that support high-volume experimentation and user engagement flows spanning from the mobile client to backend services Drive the Cross-Platform Strategic Vision and roadmap, ensuring our architecture supports high-volume experimentation, rapid iteration and future business needs Promote Continuous Improvement by driving architectural standards, engineering best practices, and operational excellence across multiple teams. Provide guidance to and mentor Senior Engineers and other team members, fostering a culture of technical excellence and career growth. Identify root causes of systemic issues and architectural bottlenecks, determining short-term mitigations and long term strategic resolutions. Work and intervene on the whole life cycle of the software, from high level system design to deployment and post release monitoring. Partner closely with Product Managers and Data Scientists to design technical solutions that unlock new growth opportunities and optimise user funnels. What We Look For Proven track record of technical leadership, preferably in a mobile heavy or full stack capacity Experience designing and architecting systems at scale Deep experience with A/B testing frameworks, experimentation platforms, or data intensive growth loops. High level of pragmatism; you understand when to build for scale and when to optimise for speed of learning. Positive and solution oriented mindset Strong planning and prioritisation skills, with the ability to translate high level business goals into actionable technical strategies across the stack. Ability to share product insight with stakeholders, challenge product decisions with data, and act as a bridge between Engineering, Product, and Data Science. Demonstrated capacity to clearly and concisely communicate about complex technical, architectural, and/or organisational challenges to both technical and non technical executives. Experience in working within a cross functional team and collaborative environment; ability to facilitate technical decision making and resolve conflicts across teams. Self motivated and self managing, with excellent organisational skills and a focus on high leverage work. Comfortable working with both strongly and dynamically typed languages. We value your ability to architect Plum Perks Own part of the company through stock options Private health insurance Annual training budget Plum Premium Referral scheme: earn competitive rewards Flexible approach to remote working: we encourage at least 2 days a week in one of our beautiful offices in London, Athens or Cyprus Team breakfasts and team lunches. 25 days holiday + bank holidays 45 work from anywhere days: giving you the flexibility to work your way. 2 weeks sabbatical after 4 years to take the break you deserve. Enhanced parental leave 1 paid volunteering day annuallyAnnual team trip: to a surprise destination! A fun, inclusive company culture If this sounds like you, we'd love to hear from you! Thanks, Team Plum Plum is an Equal Opportunity Employer. Plum does not discriminate on the basis of race, religion, sex, gender identity, sexual orientation, non disqualifying physical or mental disability, national origin or any other basis covered by appropriate law. All employment is decided on the basis of qualifications, merit and business need.

Fin is the AI Customer Agent company on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always on customer support across the customer journey - from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end to end across every channel, with minimal set up and integration. Fin can also be combined with our natively integrated the company help desk for one single system that is designed to meet the needs of modern day support teams. Founded in 2011, Fin became one of the fastest growing companies and remains one of the largest private software companies in the world with nearly 30,000 global businesses using our products to transform their customer support. Driven by our core values, we push boundaries, build with speed and intensity, and relentlessly deliver incredible value to our customers. What's the opportunity? The Research, Analytics & Data Science (RAD) team at Fin use data and insights to drive evidence based decision making. We are a team of data scientists and product researchers who use data - both big and small - to unlock actionable insights about our customers, our products and our business. We generate insights that build customer empathy, drive product strategy and shape products that deliver real value to our customers. If you get really excited about asking the right questions, exploring patterns in data and surfacing actionable insights that drive strategic decisions, then this role is for you. Data Scientists in RAD partner with teams across R&D to help Fin make sense of our users, our products and our business, using metrics and data. This role will enable you to drive key data projects that directly impact our customers and millions of end users who communicate via our messaging platform daily. What will I be doing? You'll partner with product teams to help them identify important questions and answer those questions with data You'll work closely with product managers, designers and engineers to develop key product success metrics, to set targets, to measure results and outcomes, and to size opportunities You'll design, build and update end to end data pipelines, working closely with stakeholders to drive the collection of new data and the refinement of existing data sources and tables. You'll partner closely with product researchers to build a holistic understanding of our customers, our products and our business. You'll influence our product roadmap and product strategy through experimentation, exploratory analysis and quantitative research You'll build and automate actionable models and dashboards You'll craft data stories and share your findings and recommendations across R&D and the broader company You'll drive and shape core RAD foundations and help us improve how the RAD org operates What skills do I need? 5+ years experience working with data to solve problems and drive evidence based decisions Excellent SQL skills and experience applying analytical and statistical approaches to problem solving Proven track record of initiating and delivering actionable analysis and insights that drive tangible impact with minimal supervision Excellent communication skills (technical and non technical) and a focus on driving impact Strong growth mindset and sense of ownership. Innate passion and curiosity Experience with a scientific computing language such as R or Python Bonus skills & attributes Experience with BI/Visualization tools like Tableau, Superset and Looker Experience with data modeling and ETL pipelines Experience working with product teams Experience leveraging AI tools to boost efficiency and creativity across the data science workflow - from ideation and coding to analysis and communication Benefits We are a well treated bunch, with awesome benefits! If there's something important to you that's not on this list, talk to us! Competitive salary and equity in a fast growing start up We serve lunch every weekday, plus a variety of snack foods and a fully stocked kitchen Regular compensation reviews - we reward great work Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents Open vacation policy and flexible holidays so you can take time off when you need it Paid maternity leave, as well as 6 weeks paternity leave for fathers, to let you spend valuable time with your loved ones MacBooks are our standard, but we're happy to get you whatever equipment helps you get your job done Equal Employment Opportunity Fin values diversity and is committed to a policy of Equal Employment Opportunity. Fin will not discriminate against an applicant or employee on the basis of race, color, religion, creed, national origin, ancestry, sex, gender, age, physical or mental disability, veteran or military status, genetic information, sexual orientation, gender identity, gender expression, marital status, or any other legally recognized protected basis under federal, state or local law.

The Opportunity We're seeking a passionate Data Scientist to own the end-to-end implementation and design of data science applications for various clients. You will join a growing practice and champion and actively contribute to the growth of the discipline, enabling the ongoing growth of the data science capability. You'll join a talented team of dynamic and driven professional problem solvers; creative thinkers and solutions builders who thrive on helping clients meet the most exciting digital transformation challenges. Make a difference and advance your career by helping deliver some of the UK's most important projects, making the world a smarter, safer, greener, and healthier place. At a certified Great Place to Work you'll experience a dynamic and nurturing environment that rewards initiative and flexibility and enjoy a career path tailored to your own aspirations. Key Accountabilities and Responsibilities Senior Data Scientists enable the design, development, integration and testing of complex, high quality data science solutions and services to meet user needs, continually improving the application of best practice patterns, methods and tools. This includes: Build effective working relationships with client counterparts in your practitioner domain, and those of a partner/3rd party organisation. Own the end-to-end implementation and design of data science models/components, seeking guidance and input from Lead and Principal Data Scientists where necessary. Help structure and provide technical assurance for the work of less experienced practitioners, enabling them to maximise quality and velocity. Monitor the application of the methods and requirements, pro-actively managing technical risks and issues. Collaborating with practitioners from other disciplines (e.g. UCD, Engineering) to ensure the solution meets user and business needs. Take technical responsibility for the delivery of high-quality data science services on smaller engagements, across all stages (design, build, test, deploy, operate and continually improve), in line with best practice. Work with Delivery Managers to inform estimates for research and development activities, enabling them to plan technical activities, including how teams and work should be structured. Proactively identify and help mitigate technical risks, issues, assumptions and dependencies. Maintain relevant, up-to-date practitioner skills through training and accreditation, including a domain-relevant accreditation/certification at professional level. Being an active member of the Data Science discipline, identifying area for growth across the business, and providing coaching for less experienced practitioners. Requirements Background in Agile delivery environments, delivering software solutions in controlled increments (e.g., following Scrum, Agile Delivery phases, etc.). Experience working with cloud-based solutions and technologies (Google Cloud Platform, AWS, Azure). Hands on knowledge of designing and implementing solutions capable of handling sensitive data (e.g., Personally Identifiable Information). Strong knowledge of a programming languages for data science (Python, R, etc.) including best practices using this language to write robust software. An understanding of data governance and best practices to ensure data protection. Experience planning technical activities and structuring work for a team. Being able to provide commercially robust estimates of development activities. Experience providing practitioner guidance to junior colleagues and peers. Understanding of how to operationalise and deploy a Data Science solution in a live environment. A bachelor's degree in a STEM field. Desirable skills and experience Experience working in a professional services/consultancy environment preferred. Experience solving natural language processing problems. Experience creating generative AI applications, such as chatbots or RAG retrieval systems. Stay up to date with cutting edge of AI, reading research papers, attending conferences, etc. Ability to work effectively across multiple teams and projects. Ability to explain and simplify complex information to stakeholders, gathering and translating business requirements, anticipating any obstacles to information flow. Understanding of different databases (Relational and NoSQL) and optimising queries for effective data manipulation. A master's degree or PhD in a STEM field. Personal Qualities You are hands on, working within a team to solve complex software and feature problems. Inquisitive, using critical thinking to ask lots of questions, overcome biases, break assumptions and consider different perspectives. Strong analytical and problem-solving skills. Excellent communication and interpersonal skills. Detail-oriented with a focus on accuracy. Able to plan and organise your own work, effectively negotiating priorities crossing multiple teams across the business. Able to collaborate with other areas of the business to solve problems. Able to quickly learn and adapt to new technologies. Benefits Our benefits package compliments our highly competitive salaries and our great working environment. We believe that our people should be properly rewarded for their commitment to the continued success of our business through a comprehensive and flexible range of benefits. These can include: InformedACADEMY - We offer excellent career development opportunities through our award winning personal and professional development programmes, including support with professional certifications. Industry leading health and wellbeing plan - We partner with several wellbeing support functions to cater to each individual's need, including 24/7 GP services, mental health support and physical health support. Hybrid working Private Health Care Cover Generous life assurance cover Gym Membership Monthly office lunch Onsite massage sessions 25 paid working days holiday per year plus bank holidays Sabbatical Leave Scheme Enhanced Maternity Leave and Pay Enhanced Paternity Leave and Pay Company Pension Contribution Profit Share Scheme Payment of professional subscriptions Generous referral scheme with no limits on the number of referrals Salary Sacrifice scheme Qualifying period applies

About the rolex Imagine stepping into a role where your code directly empowers the world's largest enterprises to safely adopt superintelligence. As a software engineer, generative ai at the company, you'll be at the forefront of expanding human capacity by building the secure, scalable foundation that allows our generative AI solutions to thrive in complex corporate environments. The impact of this work is massive - for example, in the consumer packaged goods industry alone, our AI adoption is driving 69% revenue increases and 72% cost reductions. This role is designed for a well rounded engineering generalist who leans heavily into generative AI while bringing a whole systems mindset to architectural design. If you thrive on proactivity without red tape and love owning projects from proposal to deployment, you'll shape the future of AI and contribute to a product that's changing how the world works. This is a hybrid role based out of our San Francisco, New York City, or London hubs. You'll report to an engineering director or a senior engineering manager. We are open to hiring for this role at multiple levels, from senior to staff software engineer, with compensation ranges scaled to match your experience and expertise. What you'll do Design and develop robust, secure, and scalable generative AI services and applications using Python and modern frameworks to drive enterprise wide transformation Build and optimize high performance, low latency APIs and microservices to integrate advanced AI models and sophisticated agentic workflows into our core platform Act as a whole systems thinker by making meaningful system design decisions and owning the architecture of core platform components from initial proposal through production deployment Implement and maintain responsive user interfaces using technologies like React and TypeScript to deliver intuitive user experiences and bridge the gap between backend services and frontend enablement Drive proactivity without red tape by clearly communicating changes, plans, and proposals to cross functional teams and collaborating closely with product managers, data scientists, and DevOps engineers Partner with DevOps teams to build continuous deployment, logging, and monitoring systems that ensure top tier performance, security, and reliability across distributed workloads What you need 3 5+ years of hands on experience as a software engineer with a strong emphasis on Python development in production environments Proven expertise in building and deploying generative AI applications, leveraging LLMs, vector databases like Pinecone, Weaviate, or pgvector, and modern open source agentic frameworks Practical experience with microservices architecture, RESTful APIs, cloud platforms such as AWS, GCP, or Azure, and containerization with Docker and Kubernetes Solid grasp of modern web technologies including FastAPI, Asyncio, database systems like PostgreSQL, and hands on experience leveraging AI developer tooling like Claude, Cursor, or GitHub Copilot to accelerate your engineering workflows Exposure to enterprise architecture including practical experience implementing IAM, SSO, SAML, OAuth, OIDC, RBAC, robust security best practices, or building services for enterprise administration and billing systems A Connect mindset that thrives in collaborative settings where you actively engage with cross functional teams and mentor other engineers, a Challenge spirit that drives you to tackle complex technical hurdles and proactively suggest innovative improvements, and an Own attitude where you take full accountability for delivering high quality, resilient, and scalable code from conception to production Benefits & perks (UK full time employees) Generous PTO, plus company holidays Comprehensive medical and dental insurance Paid parental leave for all parents (16 weeks) Fertility and family planning support Early detection cancer testing through Galleri Competitive pension scheme and company contribution Annual work life stipends for: Wellness stipend for gym, massage/chiropractor, personal training, etc. Learning and development stipend Company wide off sites and team off sites Competitive compensation and company stock options

What's the opportunity? The Research, Analytics & Data Science (RAD) team at Fin use data and insights to drive evidence based decision-making. We're a team of data scientists and product researchers who use data - both big and small - to unlock actionable insights about our customers, our products and our business. We generate insights that build customer empathy, drive product strategy and shape products that deliver real value. If you get excited about asking the right questions, exploring patterns in data and turning insights into action, this role is for you. Data Scientists in RAD partner with teams across R&D to help Fin make sense of our users, our products and our business, using metrics, data and analysis. This role will enable you to drive key data projects that directly impact our customers and millions of end users who communicate via our messaging platform daily. What will I be doing? You'll partner with product teams to help them identify important questions and answer those questions with data You'll work closely with product managers, designers and engineers to develop key product success metrics, to set targets, to measure results and outcomes, and to size opportunities You'll design, build and update end-to-end data pipelines, working closely with stakeholders to drive the collection of new data and the refinement of existing data sources and tables. You'll partner closely with product researchers to build a holistic understanding of our customers, our products and our business. You'll influence our product roadmap and product strategy through exploratory analysis and quantitative research Increasingly, you will also: Use AI-assisted tools (e.g. Claude Code, Cursor) to accelerate analysis, coding and insight generation Identify opportunities to automate your own workflows and reduce time spent on repetitive tasks Build scalable data products (dashboards, models, internal tools) that enable stakeholders to self-serve insights Help teams interact more directly with data (e.g. through better abstractions, semantic layers, or AI-powered interfaces) Raise the bar for how AI is used within RAD- sharing patterns, workflows and best practices Craft clear, compelling data stories and communicate recommendations across R&D and the broader company Contribute to and shape core RAD foundations, improving how the team operates What skills do I need? 5 + years experience working with data to solve problems and drive evidence-based decisions Strong SQL skills and solid grounding in statistics Experience working closely with product teams Proven track record of delivering actionable insights that drive measurable impact with minimal supervision Strong product intuition, business acumen and ability to connect analysis to strategy Excellent communication skills (technical and non-technical), with a focus on driving decisions and outcomes Strong ownership, curiosity and growth mindset Experience with a scientific computing language (e.g. Python) And increasingly important: Ability to effectively use AI tools (e.g. Claude Code, Cursor) to accelerate and improve your work A mindset of automation and leverage - looking for ways to scale your impact beyond one-off analyses Comfort working in ambiguous, fast-evolving environments where tools and workflows are rapidly changing Bonus skills & attributes Experience with data modeling and ETL pipelines (esp dbt) Experience building internal tools, data products or self-serve analytics capabilities Experience leveraging AI across the data workflow - from ideation and coding to analysis and communication Benefits We are a well treated bunch, with awesome benefits! If there's something important to you that's not on this list, talk to us! Competitive salary and equity in a fast-growing start-up Unlimited access to Claude Code and best-in-class AI tools; experimentation & building is encouraged & celebrated. We serve lunch every weekday, plus a variety of snack foods and a fully stocked kitchen Regular compensation reviews - we reward great work Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents Open vacation policy and flexible holidays so you can take time off when you need it Paid maternity leave, as well as 6 weeks paternity leave for fathers, to let you spend valuable time with your loved ones MacBooks are our standard, but we're happy to get you whatever equipment helps you get your job done Fin values diversity and is committed to a policy of Equal Employment Opportunity. Fin will not discriminate against an applicant or employee on the basis of race, color, religion, creed, national origin, ancestry, sex, gender, age, physical or mental disability, veteran or military status, genetic information, sexual orientation, gender identity, gender expression, marital status, or any other legally recognized protected basis under federal, state, or local law.

Senior / Lead Data Scientist, Product Analytics Office: United Kingdom Remote: UK About the company About Cleo At Cleo, we're not just building another fintech app. We're embarking on a mission to fundamentally change humanity's relationship with money. Imagine a world where everyone, regardless of background or income, has access to a hyper-intelligent financial advisor in their pocket. That's the future we're creating. Cleo is a rare success story: a profitable, fast growing unicorn with over $300 million in ARR and growing over 2x year-over-year. This isn't just a job; it's a chance to join a team of brilliant, driven individuals who are passionate about making a real difference. We have an exceptionally high bar for talent, seeking individuals who are not only at the top of their field but also embody our culture of collaboration and positive impact. If you're driven by complex challenges that push your expertise, the chance to shape something truly transformative, and the potential to share in Cleo's success as we scale, while growing alongside a company that's scaling fast, this might be your perfect fit. Follow us on LinkedIn to keep up to date with new product features and insights from the team. About the role As a Senior / Lead Data Scientist in Product Analytics you'll be at the centre of strategic decision making within your team. Working as part of a cross functional squad alongside product managers, designers, and engineers, you'll apply your expertise to drive the future of what we build at Cleo. You will leverage rich user data and sophisticated analytical techniques to see your insights turned into real products. You'll also sit within the wider data science function here at Cleo; a hotshot team of 80 Product Analysts, Analytics Engineers, and Machine Learning Engineers, with significant industry experience that are at the heart of everything we do at Cleo. We are looking for a self starter, focused on results, with a demonstrated success in using analytics to drive the understanding, growth, and success of a product. What you'll be doing Conducting deep dive analysis in your product domain to understand user behaviour Working with Product, Machine Learning, Design, and Engineering team members in your area to build an insight driven product strategy that leads to high impact outcomes. Influencing the roadmap of your team through presentation of data based recommendations Defining how we quantitatively evaluate success, setting KPIs, designing tracking to measure what really matters Conducting regular A/B tests and causal analyses to determine the impact of product changes on success metrics Building models of user segmentation, marketing attribution, customer lifetime value, etc. Working with Analytics Engineering to prioritise data modelling needs in your area as well as directly contributing to our transformed data codebase What we're looking for 5+ years of experience doing quantitative analysis within a digital product environment Experience conducting large scale A/B experiments and interpreting results to drive product and business decisions Ability to define new product metrics from complex, unstructured data Excellent SQL skills Fluency in Python and its application in data analysis is a nice to have, but not essential Knowledge of statistics (e.g. hypothesis testing, regressions) Strong communication skills, with the ability to work fluidly across technical and non technical teams. Hands on experience with BI tools (e.g. Looker, Mode, Tableau) and data workflow tools (dbt, Airflow). A bias for action and ownership, you're excited to build from scratch, own it end to end, and deliver value fast. What do you get for all your hard work? A competitive compensation package (base + equity) with termly reviews, aligned to our OKR planning cycles. This is an AX3 or AX4 level role. AX3 banding: £74,266 - £96,126 Hybrid London or £69,699 - £90,657 UK Remote AX4 banding: £94,059 - £119,128 Hybrid London or £88,938 - £113,489 UK Remote Work at one of the fastest growing tech startups, backed by top VC firms, Balderton & EQT Ventures A clear progression plan. We want you to keep growing. That means trying new things, leading others, challenging the status quo and owning your impact. Always with our complete support. Flexibility. We can't fight for the world's financial health if we're not healthy ourselves. We work with everyone to make sure they have the balance they need to do their best work. Work where you work best. We're a globally distributed team. If you live in London, we have a hybrid approach, we'd love you to spend one day a week or more in our beautiful office. If you're outside of London, we'll encourage you to spend a couple of days with us a few times per year. And we'll cover your travel costs, naturally. Other benefits Company wide performance reviews every 4 months Generous pay increases for high performing team members Equity top ups for team members getting promoted 25 days annual leave a year + public holidays (+ an additional day for every year you spend at Cleo, up to 30 days) 6% employer matched pension in the UK Private Medical Insurance via Vitality, dental cover, and life assurance Enhanced parental leave 1 month paid sabbatical after 4 years at Cleo Regular socials and activities, online and in person We'll pay for your OpenAI subscription Online mental health support via Spill Workplace Nursery Scheme And many more! Welcoming everyone We strongly encourage applications from people of colour, the LGBTQ+ community, people with disabilities, neurodivergent people, parents, carers, and people from lower socio economic backgrounds. If there's anything we can do to accommodate your specific situation, please let us know.

About the role We're looking for a Senior Software Engineer to join our cutting edge product, Frontier, working within the Platform Core product squad. In this role, you'll be immersed in hands on work, tackling complex real world challenges using state of the art technology. From optimising multinational supply chain logistics to reducing time to market for clinical trials and supporting sustainability goals in various industries, Frontier empowers organisations to make informed decisions through AI driven insights. Join us on this exciting journey of transforming decision making with AI and machine learning, revolutionising how businesses thrive utilising Decision Intelligence. What you will be doing Collaborating with other Engineers in the team to develop and implement AI driven software solutions. Conducting code reviews & pair programming with junior members of the team, directly impacting customer projects and outcomes. Getting the opportunity to work in diverse domains, expanding your industry knowledge and gaining experience with cutting edge technologies. Working in an Agile environment with cross functional teams, including data scientists, project managers, and business stakeholders, to understand customer needs and translate them into technical requirements. What we are looking for Demonstrable experience programming in Python Experience building maintainable code for software products Experience working with data scientists and Machine Learning Experience and understanding of Data Structures and Algorithms Experience leading junior engineers Outstanding verbal and written communication skills, ensuring inclusivity in all interactions. What we can offer you The Faculty team is diverse and distinctive, and we all come from different personal, professional and organisational backgrounds. We all have one thing in common: we are driven by a deep intellectual curiosity that powers us forward each day. Faculty is the professional challenge of a lifetime. You'll be surrounded by an impressive group of brilliant minds working to achieve our collective goals. Our consultants, product developers, business development specialists, operations professionals and more all bring something unique to Faculty, and you'll learn something new from everyone you meet.

Job Type: Permanent. Build a brilliant future with the company. Principal Machine Learning Engineer Location London / York Why the company London Market The company London Market sits at the centre of global specialist insurance, tackling some of the most complex and unusual risks in the world. These are not commoditised problems, they demand deep expertise, strong judgement, and increasingly, sophisticated data and machine learning capabilities. We have a strong track record of putting AI into real production use, from augmenting underwriting decisions to shaping future market standards through partnerships and market first innovation. This is an environment where advanced ML systems are expected to operate reliably, safely, and at scale, not remain in experimentation. You'll join a culture that values technical excellence, ownership, and courage, where senior individual contributors are trusted to set direction, challenge thinking, and build platforms that matter. For a Principal Machine Learning Engineer, this is a chance to work on high impact ML systems, influence how AI is adopted across the London Market, and help shape the future of insurance. Role Purpose As a Principal Machine Learning Engineer (MLE), you bring a wealth of experience in building, scaling, and operating production machine learning systems, and use that experience to provide deep technical leadership across machine learning engineering and MLOps. You play a key role in shaping the architectural strategy for production ML systems and the ML Platform, working closely with Data Science, Engineering, and Platform teams to define patterns, standards, and tooling that enable reliable, repeatable delivery at scale. Through hands on contribution, design leadership, and technical mentorship, you help teams navigate complex technical decisions and build robust, maintainable systems. A central focus of the role is enabling the organisation to move quickly without sacrificing quality, evolving the ML platform, supporting the transition from experimentation to production, and helping teams adopt modern engineering practices. This includes championing the effective and responsible use of AI assisted development tools as part of a broader approach to improving developer experience, system quality, and long term sustainability. Success in this role comes from the practical application of deep experience, strong architectural thinking, and the ability to help others build better systems that deliver real business value. Key Responsibilities Technical Leadership & Ownership (Individual Contributor) Act as the technical lead for Machine Learning Engineering and MLOps across London Market. Technically lead the most complex and business critical ML systems, from architectural design through to production operation. Define and evolve production ML patterns and best practices, covering deployment, orchestration, monitoring, retraining, and decommissioning. Lead deep technical decision making, balancing scalability, reliability, security, and developer experience. Contribute hands on to critical systems, frameworks, and platform components where the complexity or impact demands it. Define best practices and guardrails for the use of AI assisted coding tools, ensuring they are used to improve productivity and code quality without compromising maintainability or operational safety. Lead by example in applying AI assisted development techniques (e.g. for prototyping, refactoring, and accelerating complex engineering work) with strong engineering judgement. ML Platform Strategy & Build Out Partner closely with Group and Platform teams to design, build, and evolve the ML Platform, ensuring it supports: Reusable and scalable deployment patterns CI/CD for machine learning Full model lifecycle management Monitoring, observability, and alerting Secure and compliant operation Shape platform standards and interfaces that enable consistent ML delivery across squads and value streams. Lead technical spikes and proof of concepts to evaluate new tools, approaches, and architectural patterns. Influence developer tooling choices so that AI assisted coding tools integrate safely with CI/CD, testing, and governance workflows. Ensure the platform enables fast, safe experimentation while supporting robust, long lived production systems. Governance, Reliability & Commercial Impact Ensure ML systems meet architecture, security, compliance, and operational standards. Define and implement robust frameworks for monitoring technical health, model performance, and commercial impact of ML systems in production. Champion operational excellence across ML services, including monitoring, alerting, incident management, and post incident learning. Ensure clear ownership and lifecycle management for models and ML backed services. Promote responsible use of automation and AI assisted tooling in safety critical or regulated contexts. Collaboration & Influence Work closely with the Data Science team to ensure a smooth and repeatable transition from experimentation to production. Collaborate with software engineers, product managers, and business stakeholders to deliver end to end ML driven solutions. Act as a senior technical voice in design reviews, architecture forums, and strategic discussions. Influence technical direction and standards through expertise, credibility, and collaboration rather than line management. Technical Mentorship & Capability Development Provide hands on technical mentorship to Machine Learning Engineers and Data Scientists. Raise engineering standards by sharing best practices, patterns, and lessons learned from real production systems. Coach teams on the effective and critical use of AI assisted coding tools, reinforcing the importance of code review discipline, testing, and long term maintainability. Contribute to technical hiring, assessment, and onboarding from a senior engineering perspective. Help shape long term capability by identifying gaps in tooling, skills, and platform maturity. What You'll Bring Experience & Background Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field (or equivalent experience). Extensive experience as a senior or principal Machine Learning Engineer delivering production ML systems at scale. Proven track record of owning or shaping ML platforms, MLOps frameworks, or critical ML infrastructure. Experience operating in complex, cross functional environments (insurance or financial services experience is advantageous but not essential). Technical Expertise Exceptional Python skills in a machine learning engineering context, with strong software engineering fundamentals (OOP, testing, design patterns). Deep experience building, deploying, and operating production ML systems, including: Online and batch model serving Monitoring, alerting, and observability Retraining and lifecycle management Strong understanding of core data science concepts, sufficient to: Review and challenge modelling approaches Ensure models are production ready and correctly evaluated Hands on experience with a major cloud platform (AWS, GCP, or Azure), including containerised deployments. Expert knowledge of MLOps and CI/CD, including: Git based workflows Infrastructure as Code (e.g. Terraform) Automated testing and deployment pipelines Strong operational mindset, including APIs, logging, monitoring, reliability, and incident response. Working knowledge of SQL and integration of ML services into wider data and application ecosystems. Experience using AI assisted coding tools in a production engineering context, with a clear understanding of their benefits, limitations, and risks. Why Join Us? This is an opportunity to shape the future of machine learning engineering at the company, build a high performing sub chapter, and influence strategic decisions, while staying close to the craft you love. You'll have the autonomy to set standards, mentor talent, and explore emerging technologies, all within a collaborative and forward thinking environment. Work with amazing people and be part of a unique culture.

Senior Full Stack Developer - 6-month Fixed Term Contract Singer Instruments empower scientists in laboratories in over 60 countries to accelerate their research efforts on global challenges. We're looking for a Senior Full Stack Developer to take ownership of translating complex product discovery specifications into production grade, highly scalable features for our new AI SaaS platform. The Role Supported by a newly secured public funding grant, we are initiating an intensive engineering phase to transition a laboratory-validated technical imaging technology from a Proof of Concept (TRL 4) into a commercially viable TRL 7 multi tenant AI SaaS platform. The platform leverages advanced machine learning models to automate high precision feature detection, image normalisation, and automated data analysis. You will be responsible for designing, implementing, and deploying both the user facing client applications and the robust server side architectures for the SaaS platform. What you'll bring to our team (key contributions) You will take ownership of the end to end technical construction of the SaaS web application, translating complex product discovery specifications into production grade, highly scalable features. Design, develop, and maintain robust, scalable software solutions across the entire technology stack. Build and maintain secure RESTful APIs, manage database schemas, and optimise server side logic. Implement responsive, intuitive user interfaces and deliver a seamless user experience using modern frameworks. Lead code reviews, enforce best practices, and provide technical guidance and mentorship to junior members of the team. Work closely with Product & Project managers, UX/UI designers, and other engineers in an Agile environment. Who you are (essential skills & attributes) Proven experience building, scaling, and maintaining multi tenant SaaS platforms, including user subscription workflows and strict multi tenant data isolation. 5+ years of commercial full stack software engineering experience. Extensive, expert level experience with cloud platforms, specifically Amazon Web Services (AWS). You must be comfortable managing, scaling, and architecting systems using core services like AWS EC2, AWS Lambda, and related infrastructure. Strong proficiency in both Python and Node.js to build secure, scalable, and resilient server side components. Deep expertise in React and modern state management tools for highly interactive, intuitive user interfaces. Advanced experience designing schemas and optimising complex queries in relational databases common on AWS, particularly PostgreSQL or MySQL (ideally via Amazon RDS or Amazon Aurora). Experience using tools like Terraform, AWS CloudFormation, or AWS CDK to define and deploy infrastructure programmatically. Strong ability to work with third party vendors, external APIs, and strategic tech partners to smoothly integrate external systems, software components, or infrastructure tools. Familiarity with leveraging AI driven engineering tools (e.g., GitHub Copilot, Claude) to optimise development speed and team delivery. Extensive experience working within fast paced Agile delivery teams using frameworks such as Scrum/Kanban, and expert level proficiency with project management tools, specifically Jira and Confluence. Intelligent AI Integration: Hands on experience embedding AI capabilities directly into platform features to drive user efficiency, specifically: Building conversational chatbots and intelligent virtual assistants. Developing automated data analysis pipelines to surface business insights. Implementing predictive text, smart autocompletion, or generative content tools. Hands on experience building automated build, test, and deployment workflows using GitHub Actions, GitLab CI, or AWS CodePipeline. Knowledge of implementing secure authentication protocols and protecting against vulnerabilities. Understanding of data protection regulations such as GDPR and security frameworks like SOC 2. Experience setting up observability tools like Datadog, New Relic, or AWS CloudWatch to track system health and latency. Experience writing thorough automated tests using Jest, React Testing Library, Cypress, or Playwright. You will bring 5+ years of commercial full stack software engineering experience to the role. Crucially, while this outlines typical pathways, your unique journey matters more than just a qualification. Mandatory Grant Compliance & Eligibility To comply with the strict terms of our public funding body, all applicants must meet the following baseline criteria: Sovereignty Status: Candidates must possess an absolute, unrestricted right to work in the UK (UK Nationals preferred). We cannot offer visa sponsorship or international remote working arrangements. Geographic Restriction: Every hour of work and line of code must be executed strictly on UK soil. Working from overseas is contractually prohibited.

PURPOSE A Senior Product Manager is responsible for leading the development and execution of the product strategy within a Squad towards desired outcomes. Product Managers work as part of a product trio, consisting of a Product Designer and Engineering Manager, across the product lifecycle to solve real problems for customers in ways that meet the needs of the business. This individual will report to the Product Lead - Artificial Intelligence and work cross-functionally to collaborate with all areas of the business. The product manager's role is to take holistic responsibility for their product area to define success and create the framework for decision-making. A product manager is responsible for evaluating opportunities and determining what gets built by the Squad and delivered to customers and users. This means managing the product backlog and ensuring what gets built is truly worth building. COMPETENCIES Technical Competencies Product management - Manage the full product life cycle to ensure that customer/user needs are met, including the use of various inputs to understand needs and opportunities, and ownership of the product backlog. Global approach - encourage a global view on initiating and delivering SW to meet global needs, laws and regulations. AI / ML - expertise in SW products enabled via one or more of the following technologies: artificial intelligence/machine learning, medical image analysis, NLP, big data, etc. Other Competencies (Behavioural, Leadership) Strategic mindset - Seeing ahead to future possibilities and translating them into breakthrough strategies. Cultivates innovation - Creating new and better ways for the organisation to be successful. Drives results - Consistently achieving results, even under tough circumstances. Decision quality - Making good and timely decisions that keep the organisation moving forward. Balances stakeholders - Anticipating and balancing the needs of multiple stakeholders. Collaborates - Building partnerships and working collaboratively with others to meet shared objectives. Instills trust - Gaining the confidence and trust of others through honesty, integrity, and authenticity. Situational adaptability - Adapting approach and demeanour in real time to match the shifting demands of different situations. MINIMUM QUALIFICATIONS (To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the education, experience, knowledge, skill and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.) Education Bachelor's degree or higher in Computer Sciences, Business Administration, Engineering, or other related field (or equivalent and related experience). Experience 8-10 years of experience in software product management, either as a product manager, product owner, data scientist, software engineer, or in a role associated with software development 5-8 years of experience in building and clearing Software as Medical Devices, with knowledge of Medical Devices Quality Management and Product Lifecycle Management processes 5+ years of experience working on products across the full product lifecycle (conception, development, go-to-market, and post launch support). 5+ years of experience in agile software development methodologies or related activities Strong communication skills and ability to influence colleagues. Experience leading complex, cross-functional projects. Ability to influence and drive results in cross-functional teams. Skills Team-oriented Fluent in English - written and verbal. Excellent communication and interpersonal skills Strong problem-solving and analytical skills Ability to manage multiple global projects simultaneously Strong leadership and decision-making skills Passion for technology and for delivering high-quality products What makes you stand out: Global experience - ability to empathise with different cultures and organisational set ups. Deep understanding of healthcare, endoscopy, medical imaging products and clinical workflows is desirable. Proven track record of product ownership from concept to broad launch in the healthcare industry MS, or PhD or MBA or relevant advanced degree Additional fluency in a European Language (like German, Spanish, etc.) or Japanese is an asset.

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.