Processing thousands of energy data points per second from diverse operational sources, handling massive volumes of energy data while running sophisticated classification and anomaly detection models in real-time, maintaining comprehensive data lineage, and delivering insights through high-performance platforms used by energy operators globally requires exceptional engineering and scientific expertise. This processing demands models that can withstand the scrutiny of energy analysts and traders, operations teams, and regulatory bodies, with the performance, stability, and reliability that critical energy systems require. The Data Platform Team is responsible for all machine learning operations across our energy data ecosystem. We work with everything from raw sensor data from millions of energy assets to complex operational datasets, generating high-value predictions such as equipment failure detection, energy demand forecasting, operational anomaly identification, predictive maintenance scheduling, and system optimization recommendations. The team has built a comprehensive suite of statistical and machine learning models that enable us to provide the most accurate and actionable insights into energy operations. We take pride in applying cutting edge research to real world energy challenges in a robust, scalable, and maintainable way. The quality of our models is continuously validated by experienced in house energy analysts and traders and domain experts to ensure reliability of our predictions. You'll be instrumental in designing and building ML infrastructure and applications to propel the design, deployment, and monitoring of existing and new ML pipelines and models. Working with software engineers, data scientists, and energy analysts and traders, you'll help bridge the gap between research experiments and production energy systems by ensuring 100% uptime and bulletproof fault tolerance of every component of our ML platform. You Are: Experienced in building and deploying distributed scalable ML pipelines that can process large volumes of energy data daily using Kubernetes and MLflow With solid machine learning engineering fundamentals, fluent in Python, PyTorch, and XGBoost Skilled in developing classification models and anomaly detection systems for production environments Capable of implementing comprehensive data lineage tracking and model governance systems Driven by working in an intellectually engaging environment with top energy analysts and traders and technology experts, where constructive challenges and technical debates are encouraged Excited about working in a dynamic environment: not afraid of complex energy challenges, eager to bring new ML innovations to production, and a positive can do attitude Passionate about mentoring team members, helping them improve their ML engineering skills and grow their careers Experienced with the full ML model lifecycle, including experiment design, model development, validation, deployment, monitoring, and maintenance Awesome If You: Have experience in the energy sector or understanding of energy systems and operations Have practical experience with AWS services (SageMaker, S3, EC2, Lambda, etc.) Have experience with infrastructure as code tools (Terraform, CloudFormation) Have experience with Apache Kafka and real time streaming frameworks Are familiar with observability principles such as logging, monitoring, and distributed tracing for ML systems Have experience with transformer architectures and generative AI applications in operational contexts Have experience with time series analysis and forecasting techniques relevant to energy applications Are knowledgeable about data privacy regulations and compliance frameworks in the energy sector Benefits Enjoy flexible hybrid working - split your time between home and our office, with the freedom to work where you're most productive. A vibrant, diverse company pushing ourselves and the technology to deliver beyond the cutting edge A team of motivated characters and top minds striving to be the best at what we do at all times Constantly learning and exploring new tools and technologies Acting as company owners (all Vortexa staff have equity options)- in a business savvy and responsible way Motivated by being collaborative, working and achieving together Private Health Insurance offered via Vitality to help you look after your physical health Global Volunteering Policy to help you 'do good' and feel better
11/05/2026
Full time
Processing thousands of energy data points per second from diverse operational sources, handling massive volumes of energy data while running sophisticated classification and anomaly detection models in real-time, maintaining comprehensive data lineage, and delivering insights through high-performance platforms used by energy operators globally requires exceptional engineering and scientific expertise. This processing demands models that can withstand the scrutiny of energy analysts and traders, operations teams, and regulatory bodies, with the performance, stability, and reliability that critical energy systems require. The Data Platform Team is responsible for all machine learning operations across our energy data ecosystem. We work with everything from raw sensor data from millions of energy assets to complex operational datasets, generating high-value predictions such as equipment failure detection, energy demand forecasting, operational anomaly identification, predictive maintenance scheduling, and system optimization recommendations. The team has built a comprehensive suite of statistical and machine learning models that enable us to provide the most accurate and actionable insights into energy operations. We take pride in applying cutting edge research to real world energy challenges in a robust, scalable, and maintainable way. The quality of our models is continuously validated by experienced in house energy analysts and traders and domain experts to ensure reliability of our predictions. You'll be instrumental in designing and building ML infrastructure and applications to propel the design, deployment, and monitoring of existing and new ML pipelines and models. Working with software engineers, data scientists, and energy analysts and traders, you'll help bridge the gap between research experiments and production energy systems by ensuring 100% uptime and bulletproof fault tolerance of every component of our ML platform. You Are: Experienced in building and deploying distributed scalable ML pipelines that can process large volumes of energy data daily using Kubernetes and MLflow With solid machine learning engineering fundamentals, fluent in Python, PyTorch, and XGBoost Skilled in developing classification models and anomaly detection systems for production environments Capable of implementing comprehensive data lineage tracking and model governance systems Driven by working in an intellectually engaging environment with top energy analysts and traders and technology experts, where constructive challenges and technical debates are encouraged Excited about working in a dynamic environment: not afraid of complex energy challenges, eager to bring new ML innovations to production, and a positive can do attitude Passionate about mentoring team members, helping them improve their ML engineering skills and grow their careers Experienced with the full ML model lifecycle, including experiment design, model development, validation, deployment, monitoring, and maintenance Awesome If You: Have experience in the energy sector or understanding of energy systems and operations Have practical experience with AWS services (SageMaker, S3, EC2, Lambda, etc.) Have experience with infrastructure as code tools (Terraform, CloudFormation) Have experience with Apache Kafka and real time streaming frameworks Are familiar with observability principles such as logging, monitoring, and distributed tracing for ML systems Have experience with transformer architectures and generative AI applications in operational contexts Have experience with time series analysis and forecasting techniques relevant to energy applications Are knowledgeable about data privacy regulations and compliance frameworks in the energy sector Benefits Enjoy flexible hybrid working - split your time between home and our office, with the freedom to work where you're most productive. A vibrant, diverse company pushing ourselves and the technology to deliver beyond the cutting edge A team of motivated characters and top minds striving to be the best at what we do at all times Constantly learning and exploring new tools and technologies Acting as company owners (all Vortexa staff have equity options)- in a business savvy and responsible way Motivated by being collaborative, working and achieving together Private Health Insurance offered via Vitality to help you look after your physical health Global Volunteering Policy to help you 'do good' and feel better
We're looking for a Machine Learning Engineer, junior to mid-level, to come join our impact-focused team. If you'd like to use your skills to create real-world solutions that lower carbon emissions and accelerate the energy transition, then this is the role for you. We're a friendly, supportive and fun team who care about making a difference. Sound like a role you're interested in? Take a look at an overview of the requirements below Skills in Python and Git, in particular PyTorch, and a passion for ML experimentation. 1-4 years of experience in developing deep learning models in industry or postgraduate academia. Hybrid working: 2 days in our London office. £40,000 - £60,000 (based on experience) Applications are accepted on a rolling basis, so we encourage you to apply ASAP. Unfortunately, we are unable to offer visa sponsorship for this role. At OCF, your values and passion are more important to us than if you meet every requirement listed. If this role excites you and your values are aligned, we strongly encourage you to apply. You might be exactly who we're looking for! Apply now via this link
09/05/2026
Full time
We're looking for a Machine Learning Engineer, junior to mid-level, to come join our impact-focused team. If you'd like to use your skills to create real-world solutions that lower carbon emissions and accelerate the energy transition, then this is the role for you. We're a friendly, supportive and fun team who care about making a difference. Sound like a role you're interested in? Take a look at an overview of the requirements below Skills in Python and Git, in particular PyTorch, and a passion for ML experimentation. 1-4 years of experience in developing deep learning models in industry or postgraduate academia. Hybrid working: 2 days in our London office. £40,000 - £60,000 (based on experience) Applications are accepted on a rolling basis, so we encourage you to apply ASAP. Unfortunately, we are unable to offer visa sponsorship for this role. At OCF, your values and passion are more important to us than if you meet every requirement listed. If this role excites you and your values are aligned, we strongly encourage you to apply. You might be exactly who we're looking for! Apply now via this link
Machine Learning Engineer BeyondMath is a pioneering startup, backed by top-tier VCs, on a mission to reshape the frontiers of engineering through Foundational AI models for Physics. We are replacing traditional, slow and expensive simulation methods with AI that rivals accuracy at orders of magnitude higher speed. We are moving beyond the "generic AI" hype to solve the world's hardest physical engineering challenges in automotive, aerospace, and energy. The Role As a Machine Learning Engineer, you'll play a central role in advancing our Generative Physics simulation platform. You'll work at the intersection of ML research and engineering contributing to core model development, shaping model architecture, and delivering performant systems that integrate seamlessly into our real-world design optimization workflows. You'll work closely with our ML research team, software engineers, and industry partners to deploy robust, scalable models that deliver real-world impact. Responsibilities Physics-Focused AI Model Development: Design and train deep learning models for physics simulation across aerodynamic and engineering domains. Scalability & Performance: Drive optimization efforts for model inference speed, accuracy, and robustness on large-scale industrial datasets. Geometry Representation: Research effective ways to represent geometric design variations for efficient use by machine learning models. Production Integration: Partner with engineering teams to deploy and monitor models in production-grade pipelines and tools. Architecture & Design: Contribute to design decisions around model and data architecture, tooling, and ML infrastructure. Essential Requirements Industrial Experience: Strong track record applying ML to complex real-world problems (ideally including geometry or physical systems). Foundational Knowledge: Deep understanding of machine learning theory, including optimization, generalisation, and various model architectures. Programming: Strong python skills and experience with deep learning libraries (TensorFlow/PyTorch/JAX). Communication: Ability to clearly explain complex ML concepts and research findings to both technical and non-technical audiences. Education: Master's Degree (PhD preferred) in Machine Learning, Computer Science, or a related quantitative field. Highly Desirable Aerodynamics/CFD Expertise: Familiarity with aerodynamic principles and computational fluid dynamics is a major plus. Design Optimization: Prior experience in optimization algorithms, particularly in the context of engineering design. Physics/Science ML: Experience integrating physical laws or constraints into machine learning models. Why Join Us? Full Ownership: You will have a direct seat at the table in shaping the future of a company redefining an entire industry. High Impact: Your work will directly accelerate the transition to sustainable energy and more efficient transport. Elite Team: Work alongside veterans from world-leading AI labs and engineering firms in a culture of "impact with integrity."
09/05/2026
Full time
Machine Learning Engineer BeyondMath is a pioneering startup, backed by top-tier VCs, on a mission to reshape the frontiers of engineering through Foundational AI models for Physics. We are replacing traditional, slow and expensive simulation methods with AI that rivals accuracy at orders of magnitude higher speed. We are moving beyond the "generic AI" hype to solve the world's hardest physical engineering challenges in automotive, aerospace, and energy. The Role As a Machine Learning Engineer, you'll play a central role in advancing our Generative Physics simulation platform. You'll work at the intersection of ML research and engineering contributing to core model development, shaping model architecture, and delivering performant systems that integrate seamlessly into our real-world design optimization workflows. You'll work closely with our ML research team, software engineers, and industry partners to deploy robust, scalable models that deliver real-world impact. Responsibilities Physics-Focused AI Model Development: Design and train deep learning models for physics simulation across aerodynamic and engineering domains. Scalability & Performance: Drive optimization efforts for model inference speed, accuracy, and robustness on large-scale industrial datasets. Geometry Representation: Research effective ways to represent geometric design variations for efficient use by machine learning models. Production Integration: Partner with engineering teams to deploy and monitor models in production-grade pipelines and tools. Architecture & Design: Contribute to design decisions around model and data architecture, tooling, and ML infrastructure. Essential Requirements Industrial Experience: Strong track record applying ML to complex real-world problems (ideally including geometry or physical systems). Foundational Knowledge: Deep understanding of machine learning theory, including optimization, generalisation, and various model architectures. Programming: Strong python skills and experience with deep learning libraries (TensorFlow/PyTorch/JAX). Communication: Ability to clearly explain complex ML concepts and research findings to both technical and non-technical audiences. Education: Master's Degree (PhD preferred) in Machine Learning, Computer Science, or a related quantitative field. Highly Desirable Aerodynamics/CFD Expertise: Familiarity with aerodynamic principles and computational fluid dynamics is a major plus. Design Optimization: Prior experience in optimization algorithms, particularly in the context of engineering design. Physics/Science ML: Experience integrating physical laws or constraints into machine learning models. Why Join Us? Full Ownership: You will have a direct seat at the table in shaping the future of a company redefining an entire industry. High Impact: Your work will directly accelerate the transition to sustainable energy and more efficient transport. Elite Team: Work alongside veterans from world-leading AI labs and engineering firms in a culture of "impact with integrity."
Aim high, go beyond! At Open Cosmos we are solving the world's biggest challenges from space, providing businesses, governments and researchers access to more readily available information than ever before - ready for the challenge? Then read on The CTO division is where Open Cosmos technology comes to life. Covering engineering, product development, and technical innovation, the team designs, builds, and operates the satellites, systems, and platforms that make our missions possible. It's a highly collaborative environment where ideas become real hardware, software, and data solutions that deliver impact from space. We're looking for a Machine Learning Engineer to help build the intelligent automation layer behind Open Cosmos' growing spacecraft fleet. Working within the Mission Operations Team you'll design and deliver ML-driven solutions that power anomaly detection, forecasting, operational insights and automated decision making. This is a hands on role focused on building models, pipelines and inference systems that plug directly into mission control and production automation tools. What You'll Be Doing Developing and refining models for anomaly detection, telemetry classification, forecasting and behavioural prediction Building automated data analysis pipelines for mission telemetry and production test data Integrating ML outputs into operational tools and automation frameworks across mission control and testing Preparing, cleaning and structuring datasets for training and validation Analysing trends, surfacing insights and supporting model validation and performance tracking Maintaining high standards of data quality, reliability and traceability Working with OpenOPS to embed ML driven insights into the Mission Control System Partnering with Automation Engineers to embed ML into operational and production workflows Validating model behaviour in simulated and live operational contexts Monitoring model performance and improving production systems over time Maintaining clear documentation for models, datasets and operational interfaces What You'll Bring Strong applied capability in machine learning, data science or applied AI Strong Python capability and fluency with tools such as TensorFlow, PyTorch or Scikit learn Understanding of time series modelling and anomaly detection Background deploying ML systems into production environments Familiarity with spacecraft telemetry or aerospace systems is a plus An analytical mindset and structured problem solving approach For this role you can be based in any of our locations. To apply, you must have the legal right to work in your chosen location. Please submit your application and CV in English. Why Open Cosmos? Work at the cutting edge of space technology with customers around the globe. A mission driven company making space accessible to help solve real world challenges. A diverse, ambitious, and supportive team.
09/05/2026
Full time
Aim high, go beyond! At Open Cosmos we are solving the world's biggest challenges from space, providing businesses, governments and researchers access to more readily available information than ever before - ready for the challenge? Then read on The CTO division is where Open Cosmos technology comes to life. Covering engineering, product development, and technical innovation, the team designs, builds, and operates the satellites, systems, and platforms that make our missions possible. It's a highly collaborative environment where ideas become real hardware, software, and data solutions that deliver impact from space. We're looking for a Machine Learning Engineer to help build the intelligent automation layer behind Open Cosmos' growing spacecraft fleet. Working within the Mission Operations Team you'll design and deliver ML-driven solutions that power anomaly detection, forecasting, operational insights and automated decision making. This is a hands on role focused on building models, pipelines and inference systems that plug directly into mission control and production automation tools. What You'll Be Doing Developing and refining models for anomaly detection, telemetry classification, forecasting and behavioural prediction Building automated data analysis pipelines for mission telemetry and production test data Integrating ML outputs into operational tools and automation frameworks across mission control and testing Preparing, cleaning and structuring datasets for training and validation Analysing trends, surfacing insights and supporting model validation and performance tracking Maintaining high standards of data quality, reliability and traceability Working with OpenOPS to embed ML driven insights into the Mission Control System Partnering with Automation Engineers to embed ML into operational and production workflows Validating model behaviour in simulated and live operational contexts Monitoring model performance and improving production systems over time Maintaining clear documentation for models, datasets and operational interfaces What You'll Bring Strong applied capability in machine learning, data science or applied AI Strong Python capability and fluency with tools such as TensorFlow, PyTorch or Scikit learn Understanding of time series modelling and anomaly detection Background deploying ML systems into production environments Familiarity with spacecraft telemetry or aerospace systems is a plus An analytical mindset and structured problem solving approach For this role you can be based in any of our locations. To apply, you must have the legal right to work in your chosen location. Please submit your application and CV in English. Why Open Cosmos? Work at the cutting edge of space technology with customers around the globe. A mission driven company making space accessible to help solve real world challenges. A diverse, ambitious, and supportive team.
Machine Learning Engineer - Contract Location: Nottingham, UK (Hybrid) Salary: £500 £600 p/d (depending on experience) About the Role We are seeking a skilled and motivated Machine Learning Engineer to join our growing team in Nottingham. You will be responsible for designing, building, and deploying scalable machine learning models that drive data-driven decision-making across the business. This role bridges the gap between data science and software engineering, turning prototypes into production-ready systems. Key Responsibilities Design, develop, and deploy machine learning models and pipelines in production environments Collaborate with data scientists, software engineers, and stakeholders to translate business requirements into ML solutions Optimize model performance, scalability, and reliability Build and maintain data pipelines and feature engineering workflows Monitor and retrain models to ensure continued performance over time Implement best practices for version control, testing, and CI/CD in ML systems Stay up to date with the latest advancements in machine learning and AI technologies Required Skills & Experience Strong programming skills in Python (e.g., TensorFlow, PyTorch, Scikit-learn) Experience deploying ML models using cloud platforms (AWS, Azure, or GCP) Solid understanding of machine learning algorithms, data structures, and software engineering principles Experience with data pipelines, APIs, and microservices architecture Familiarity with containerization tools such as Docker and orchestration tools like Kubernetes Strong problem-solving skills and attention to detail Desirable Skills Experience with big data technologies (e.g., Spark, Hadoop) Knowledge of MLOps practices and tools (e.g., MLflow, Kubeflow) Experience working with NLP, computer vision, or recommendation systems Understanding of data governance and security best practices Qualifications Bachelor s or Master s degree in Computer Science, Data Science, Machine Learning, or a related field (or equivalent experience) What We Offer Competitive rate Flexible working arrangements (hybrid/remote options) Collaborative and innovative work environment Access to cutting-edge tools and technologies How to Apply Please submit your CV and a brief cover letter outlining your experience and interest in the role.
05/05/2026
Contractor
Machine Learning Engineer - Contract Location: Nottingham, UK (Hybrid) Salary: £500 £600 p/d (depending on experience) About the Role We are seeking a skilled and motivated Machine Learning Engineer to join our growing team in Nottingham. You will be responsible for designing, building, and deploying scalable machine learning models that drive data-driven decision-making across the business. This role bridges the gap between data science and software engineering, turning prototypes into production-ready systems. Key Responsibilities Design, develop, and deploy machine learning models and pipelines in production environments Collaborate with data scientists, software engineers, and stakeholders to translate business requirements into ML solutions Optimize model performance, scalability, and reliability Build and maintain data pipelines and feature engineering workflows Monitor and retrain models to ensure continued performance over time Implement best practices for version control, testing, and CI/CD in ML systems Stay up to date with the latest advancements in machine learning and AI technologies Required Skills & Experience Strong programming skills in Python (e.g., TensorFlow, PyTorch, Scikit-learn) Experience deploying ML models using cloud platforms (AWS, Azure, or GCP) Solid understanding of machine learning algorithms, data structures, and software engineering principles Experience with data pipelines, APIs, and microservices architecture Familiarity with containerization tools such as Docker and orchestration tools like Kubernetes Strong problem-solving skills and attention to detail Desirable Skills Experience with big data technologies (e.g., Spark, Hadoop) Knowledge of MLOps practices and tools (e.g., MLflow, Kubeflow) Experience working with NLP, computer vision, or recommendation systems Understanding of data governance and security best practices Qualifications Bachelor s or Master s degree in Computer Science, Data Science, Machine Learning, or a related field (or equivalent experience) What We Offer Competitive rate Flexible working arrangements (hybrid/remote options) Collaborative and innovative work environment Access to cutting-edge tools and technologies How to Apply Please submit your CV and a brief cover letter outlining your experience and interest in the role.
Machine Learning Engineer - Deliveroo Ads Join us in our mission to transform the way people shop and eat, where impact, innovation and growth drive everything we do. Our Engineering teams tackle complex technical challenges across a global, three-sided marketplace, building and scaling systems that serve millions of customers, riders and partners every day. From real-time logistics to resilient infrastructure and marketplace optimisation, we design, build and operate technology that powers Deliveroo's growth at scale. We're looking for a Machine Learning Engineer to join our London team (working hybrid, 3 days in the office). In this role, you'll enable high-quality machine decision-making to maximise ad relevance, performance, and revenue for our global partners. Get to know our Engineering team - what drives us, how we work, and what you can expect. What You'll Be Doing You'll be joining the Ads Machine Learning team. We are a high-impact group responsible for the in-house models powering Deliveroo's advertising products, focusing on ad ranking, automated bidding, and contextual bandit-based personalisation. Here's what your day-to-day might look like: Own the end-to-end lifecycle of machine learning models used in Ads ranking, bidding, and relevance systems, from initial design to productionisation. Build robust infrastructure for monitoring, evaluation, and alerting to detect model drift or performance issues in high-throughput pipelines. Collaborate cross-functionally with Product Managers and Engineers to translate complex advertising challenges into scalable ML solutions. Embed models into low-latency systems by partnering with data scientists and engineers to ensure seamless production integration. Champion technical excellence by following best practices for ML quality, reliability, and maintainability across the team. What You'll Need to Thrive Our ideal candidate will bring strong expertise in some of these areas and curiosity to grow in others: Significant experience as an ML Engineer or Data Scientist, with a proven ability to write clean, production-grade Python code. Technical proficiency with modern engineering tools including Git, Docker, Kubernetes, and CI/CD workflows (e.g., CircleCI). Solid understanding of ML fundamentals, including supervised learning, ranking, or recommendation systems. A bias for simplicity, with a demonstrated focus on shipping work that drives measurable business impact. Strong communication skills, with the ability to work effectively in a collaborative, fast-paced team environment. Experience in Ad-Tech or auction-based systems is a plus, but not essential. Why Join Us? At Deliveroo, you'll do work that matters-solving real-world problems in a three-sided marketplace that's constantly evolving. We're food lovers, problem solvers, community builders and more, brought together by a shared drive to make things better. Working here you can expect to: Solve meaningful problems at real scale Work on a complex, always-on marketplace that impacts millions every day. See your impact, fast Ship, test and improve ideas quickly in a low-hierarchy, high-ownership environment. Grow through challenge and ownership Take on big, ambiguous problems and accelerate your career with strong support. A culture built for builders High standards, collaboration, flexible working and continuous learning. ️ Want a deeper look at how we build? Check out our Tech Blog. We aim to create a fair process that lets your skills shine-our interview typically includes 3-4 stages. Explore our Engineering Interview Guide here to help you feel confident at each stage. Our Global Structure Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we're unlocking new possibilities as one global team. Diversity, Equity and Inclusion At Deliveroo, we know that a great workplace reflects the world around us and that true diversity and inclusion make us stronger, more creative, and better at what we do. We're committed to fostering an environment where everyone can do their best work and feel they belong. We believe in equality of opportunity and welcome candidates from all backgrounds regardless of age, gender, ethnicity, disability, sexual orientation, gender identity, socio-economic background, religion, or belief. If you have a disability or long-term health condition and need support to apply for one of our roles, or if you require any reasonable adjustments during the recruitment process, please contact our recruitment team at and we'll be happy to help ensure you have a fair and equitable experience. If you're excited about solving meaningful problems at scale and growing with a supportive team, we'd love to hear from you.
05/05/2026
Full time
Machine Learning Engineer - Deliveroo Ads Join us in our mission to transform the way people shop and eat, where impact, innovation and growth drive everything we do. Our Engineering teams tackle complex technical challenges across a global, three-sided marketplace, building and scaling systems that serve millions of customers, riders and partners every day. From real-time logistics to resilient infrastructure and marketplace optimisation, we design, build and operate technology that powers Deliveroo's growth at scale. We're looking for a Machine Learning Engineer to join our London team (working hybrid, 3 days in the office). In this role, you'll enable high-quality machine decision-making to maximise ad relevance, performance, and revenue for our global partners. Get to know our Engineering team - what drives us, how we work, and what you can expect. What You'll Be Doing You'll be joining the Ads Machine Learning team. We are a high-impact group responsible for the in-house models powering Deliveroo's advertising products, focusing on ad ranking, automated bidding, and contextual bandit-based personalisation. Here's what your day-to-day might look like: Own the end-to-end lifecycle of machine learning models used in Ads ranking, bidding, and relevance systems, from initial design to productionisation. Build robust infrastructure for monitoring, evaluation, and alerting to detect model drift or performance issues in high-throughput pipelines. Collaborate cross-functionally with Product Managers and Engineers to translate complex advertising challenges into scalable ML solutions. Embed models into low-latency systems by partnering with data scientists and engineers to ensure seamless production integration. Champion technical excellence by following best practices for ML quality, reliability, and maintainability across the team. What You'll Need to Thrive Our ideal candidate will bring strong expertise in some of these areas and curiosity to grow in others: Significant experience as an ML Engineer or Data Scientist, with a proven ability to write clean, production-grade Python code. Technical proficiency with modern engineering tools including Git, Docker, Kubernetes, and CI/CD workflows (e.g., CircleCI). Solid understanding of ML fundamentals, including supervised learning, ranking, or recommendation systems. A bias for simplicity, with a demonstrated focus on shipping work that drives measurable business impact. Strong communication skills, with the ability to work effectively in a collaborative, fast-paced team environment. Experience in Ad-Tech or auction-based systems is a plus, but not essential. Why Join Us? At Deliveroo, you'll do work that matters-solving real-world problems in a three-sided marketplace that's constantly evolving. We're food lovers, problem solvers, community builders and more, brought together by a shared drive to make things better. Working here you can expect to: Solve meaningful problems at real scale Work on a complex, always-on marketplace that impacts millions every day. See your impact, fast Ship, test and improve ideas quickly in a low-hierarchy, high-ownership environment. Grow through challenge and ownership Take on big, ambiguous problems and accelerate your career with strong support. A culture built for builders High standards, collaboration, flexible working and continuous learning. ️ Want a deeper look at how we build? Check out our Tech Blog. We aim to create a fair process that lets your skills shine-our interview typically includes 3-4 stages. Explore our Engineering Interview Guide here to help you feel confident at each stage. Our Global Structure Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we're unlocking new possibilities as one global team. Diversity, Equity and Inclusion At Deliveroo, we know that a great workplace reflects the world around us and that true diversity and inclusion make us stronger, more creative, and better at what we do. We're committed to fostering an environment where everyone can do their best work and feel they belong. We believe in equality of opportunity and welcome candidates from all backgrounds regardless of age, gender, ethnicity, disability, sexual orientation, gender identity, socio-economic background, religion, or belief. If you have a disability or long-term health condition and need support to apply for one of our roles, or if you require any reasonable adjustments during the recruitment process, please contact our recruitment team at and we'll be happy to help ensure you have a fair and equitable experience. If you're excited about solving meaningful problems at scale and growing with a supportive team, we'd love to hear from you.
What you'll be doing: Have a critical role in architecting, implementing, and maintaining production grade, low latency ML services for ranking models, recommendation algorithms, and forecasting methods. Collaborate with data scientists, product managers and other teams to brainstorm best approaches for solving the problems at hand, be they product related or infrastructure related. Help design experimentations to test ideas and assess improvements to our models. Advise on data strategy to provide datasets for future data science projects. Deliver ML models with agreed engineering standards to ensure that our capabilities are resilient, scalable and future proof. Enhance our AWS native MLOps platform, and guarantee high availability and low latency inference for our models. Bring energy and positivity to the role, looking for every opportunity to learn and craft the role around our values. You'll love this role if you Have a solid foundation in traditional ML techniques and the model lifecycle, with the practical expertise to handle class imbalance, tune hyperparameters, and resolve common pitfalls like overfitting. Have demonstrable experience designing, deploying, and monitoring ML services to solve customer and business problems. Have strong programming skills in Python for delivering production ready, well structured and documented code. Have experience with large datasets and are proficient with SQL; exposure to Snowflake and dbt is a plus. Are curious about customer needs and take a pragmatic, data driven, and experimental approach to solving problems. Thrive in collaborative environments and work effectively with a range of people and teams. Bring a positive, optimistic mindset, overcoming setbacks and motivating those around you. Are keen to learn and stay up to date with the latest technologies and value sharing your knowledge with your peers. It would be great if you also have Experience working on an e commerce site or in a fast growing (preferably consumer facing) start up. Experience working in a fully remote setting. Benefits Flexible working & work from abroad 25 days holiday + your birthday + flexible bank holidays, & option to buy additional holiday each year 1 Volunteering day each year Enhanced family leave and a workplace nursery scheme A flexible training framework for every stage of your career Irresistible discounts on our products, blooms & subscriptions Share in our success with a choice to take equity options from day 1 ClassPass membership: monthly credits to spend on fitness classes, yoga and much more For more information on our perks & benefits, please see
03/05/2026
Full time
What you'll be doing: Have a critical role in architecting, implementing, and maintaining production grade, low latency ML services for ranking models, recommendation algorithms, and forecasting methods. Collaborate with data scientists, product managers and other teams to brainstorm best approaches for solving the problems at hand, be they product related or infrastructure related. Help design experimentations to test ideas and assess improvements to our models. Advise on data strategy to provide datasets for future data science projects. Deliver ML models with agreed engineering standards to ensure that our capabilities are resilient, scalable and future proof. Enhance our AWS native MLOps platform, and guarantee high availability and low latency inference for our models. Bring energy and positivity to the role, looking for every opportunity to learn and craft the role around our values. You'll love this role if you Have a solid foundation in traditional ML techniques and the model lifecycle, with the practical expertise to handle class imbalance, tune hyperparameters, and resolve common pitfalls like overfitting. Have demonstrable experience designing, deploying, and monitoring ML services to solve customer and business problems. Have strong programming skills in Python for delivering production ready, well structured and documented code. Have experience with large datasets and are proficient with SQL; exposure to Snowflake and dbt is a plus. Are curious about customer needs and take a pragmatic, data driven, and experimental approach to solving problems. Thrive in collaborative environments and work effectively with a range of people and teams. Bring a positive, optimistic mindset, overcoming setbacks and motivating those around you. Are keen to learn and stay up to date with the latest technologies and value sharing your knowledge with your peers. It would be great if you also have Experience working on an e commerce site or in a fast growing (preferably consumer facing) start up. Experience working in a fully remote setting. Benefits Flexible working & work from abroad 25 days holiday + your birthday + flexible bank holidays, & option to buy additional holiday each year 1 Volunteering day each year Enhanced family leave and a workplace nursery scheme A flexible training framework for every stage of your career Irresistible discounts on our products, blooms & subscriptions Share in our success with a choice to take equity options from day 1 ClassPass membership: monthly credits to spend on fitness classes, yoga and much more For more information on our perks & benefits, please see
Machine Learning Engineer £700-750/day overall assignment rate to umbrella Fully remote 6 month initial A FTSE 100 retail client are on the look for a Data Scientist/Machine Learning Engineer to join their data science function to drive cutting-edge ML technology across the business. Machine Learning Engineer, key skills: Significant experience working as a Data Scientist/Machine Learning Engineer Solid knowledge of SQLandPython's ecosystem for data analysis (Jupyter, Pandas, Scikit Learn, Matplotlib). GCP, VertexAI experience is desirable (developing GCP machine learning services) Timeseries forecasting Solid understanding of computer science fundamentals, including data structures, algorithms, data modelling and software architecture Strong knowledge of Machine Learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, etc.) as well as state-of-the-art research area (e.g. NLP, Transfer Learning etc.) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc.) Machine Learning Engineer, timeseries, forecasting, VertexAI, GCP Reasonable Adjustments: Respect and equality are core values to us. We are proud of the diverse and inclusive community we have built, and we welcome applications from people of all backgrounds and perspectives. Our success is driven by our people, united by the spirit of partnership to deliver the best resourcing solutions for our clients. If you need any help or adjustments during the recruitment process for any reason , please let us know when you apply or talk to the recruiters directly so we can support you.
01/09/2025
Full time
Machine Learning Engineer £700-750/day overall assignment rate to umbrella Fully remote 6 month initial A FTSE 100 retail client are on the look for a Data Scientist/Machine Learning Engineer to join their data science function to drive cutting-edge ML technology across the business. Machine Learning Engineer, key skills: Significant experience working as a Data Scientist/Machine Learning Engineer Solid knowledge of SQLandPython's ecosystem for data analysis (Jupyter, Pandas, Scikit Learn, Matplotlib). GCP, VertexAI experience is desirable (developing GCP machine learning services) Timeseries forecasting Solid understanding of computer science fundamentals, including data structures, algorithms, data modelling and software architecture Strong knowledge of Machine Learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, etc.) as well as state-of-the-art research area (e.g. NLP, Transfer Learning etc.) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc.) Machine Learning Engineer, timeseries, forecasting, VertexAI, GCP Reasonable Adjustments: Respect and equality are core values to us. We are proud of the diverse and inclusive community we have built, and we welcome applications from people of all backgrounds and perspectives. Our success is driven by our people, united by the spirit of partnership to deliver the best resourcing solutions for our clients. If you need any help or adjustments during the recruitment process for any reason , please let us know when you apply or talk to the recruiters directly so we can support you.
MACHINE LEARNING ENGINEER (MLOPS)
HYBRID/EDINBURGH OR UK REMOTE £55-60,000 PLUS BENEFITS
Based in Edinburgh, GRW Talent’s client is considered to be the leading audio-driven facial animation provider in the video-game industry. They employ detailed muscle maps for extremely accurate real-time lip-sync, trading across two recognised brands. One is an innovative platform that integrates AI with animated digital characters, enabling engaging and meaningful interactions in any language. This platform is being used to bring best-in-class digital experiences to multiple sectors, including corporate training, immersive learning, and virtual influencers.
With a culture that thrives on collaboration, creativity and pushing technological boundaries, they are committed to providing a workplace where people can grow, innovate and make an impact. They now need to recruit an experienced Machine Learning Engineer (MLOPS).
As a Senior Machine Learning Engineer (MLOps) at you will be responsible for driving the vision and implementation of MLOps pipelines and best practices. You will support the Research team by developing and maintaining the internal machine learning platform, ensuring seamless model deployment, and resolving technical issues or bugs as they arise. This role is critical in ensuring the accuracy, efficiency, and reliability of our machine learning operations, which are essential for the development and deployment of our speech animation technologies. Note that this role doesn’t involve hands-on model training. Key responsibilities include:
Drive the vision and implementation of MLOps pipelines and best practices to ensure efficient and scalable machine learning operations.
Assume a leadership role in projects, overseeing various project planning and management responsibilities.
Develop and maintain internal tools, including the machine learning platform and python libraries.
Collaborate closely with the research team to gather their requirements and provide technical support.
Implement algorithms to support research needs.
Identify, troubleshoot, and resolve technical problems and bugs promptly.
Maintain list of third party libraries dependencies to ensure compliance with information security and licensing standards.
Write and optimise production-ready code for product deployments.
Contribute to continuous integration/continuous deployment (CI/CD) for MLOps components.
Provide guidance and maintain comprehensive technical documentation to ensure knowledge sharing and operational continuity.
The relevant candidate is educated to degree calibre in Computer Science, Software Engineering or Data Science. You are a proven Machine Learning Engineer / MLOPS, with expertise in ML platform development and model deployment, experience in establishing and improving MLOps processes, strong Python development skills and experience with a machine learning toolkit, preferably PyTorch. Familiarity with any of the following domains: signal processing, speech technology, linguistics, and mathematical optimization would be a distinct advantage.
This role represent an excellent opportunity for an aspiring and experienced Machine Learning Engineer to drive the growth of a highly successful Scottish SME in the busy gaming space. Your base salary £55-60,000 is complemented by company pension, 33 days off, free food and drink in the office, self improvement budget and learning opportunities, healthcare benefits and a fun highly social culture and environment. Our client would welcome someone who wants to come into a friendly outgoing Edinburgh office, but you could also do this remotely as long as you are free to live and work in the UK.
To apply to this role please contact our recruitment partner Bruce Hydes at GRw Talent
01/06/2025
MACHINE LEARNING ENGINEER (MLOPS)
HYBRID/EDINBURGH OR UK REMOTE £55-60,000 PLUS BENEFITS
Based in Edinburgh, GRW Talent’s client is considered to be the leading audio-driven facial animation provider in the video-game industry. They employ detailed muscle maps for extremely accurate real-time lip-sync, trading across two recognised brands. One is an innovative platform that integrates AI with animated digital characters, enabling engaging and meaningful interactions in any language. This platform is being used to bring best-in-class digital experiences to multiple sectors, including corporate training, immersive learning, and virtual influencers.
With a culture that thrives on collaboration, creativity and pushing technological boundaries, they are committed to providing a workplace where people can grow, innovate and make an impact. They now need to recruit an experienced Machine Learning Engineer (MLOPS).
As a Senior Machine Learning Engineer (MLOps) at you will be responsible for driving the vision and implementation of MLOps pipelines and best practices. You will support the Research team by developing and maintaining the internal machine learning platform, ensuring seamless model deployment, and resolving technical issues or bugs as they arise. This role is critical in ensuring the accuracy, efficiency, and reliability of our machine learning operations, which are essential for the development and deployment of our speech animation technologies. Note that this role doesn’t involve hands-on model training. Key responsibilities include:
Drive the vision and implementation of MLOps pipelines and best practices to ensure efficient and scalable machine learning operations.
Assume a leadership role in projects, overseeing various project planning and management responsibilities.
Develop and maintain internal tools, including the machine learning platform and python libraries.
Collaborate closely with the research team to gather their requirements and provide technical support.
Implement algorithms to support research needs.
Identify, troubleshoot, and resolve technical problems and bugs promptly.
Maintain list of third party libraries dependencies to ensure compliance with information security and licensing standards.
Write and optimise production-ready code for product deployments.
Contribute to continuous integration/continuous deployment (CI/CD) for MLOps components.
Provide guidance and maintain comprehensive technical documentation to ensure knowledge sharing and operational continuity.
The relevant candidate is educated to degree calibre in Computer Science, Software Engineering or Data Science. You are a proven Machine Learning Engineer / MLOPS, with expertise in ML platform development and model deployment, experience in establishing and improving MLOps processes, strong Python development skills and experience with a machine learning toolkit, preferably PyTorch. Familiarity with any of the following domains: signal processing, speech technology, linguistics, and mathematical optimization would be a distinct advantage.
This role represent an excellent opportunity for an aspiring and experienced Machine Learning Engineer to drive the growth of a highly successful Scottish SME in the busy gaming space. Your base salary £55-60,000 is complemented by company pension, 33 days off, free food and drink in the office, self improvement budget and learning opportunities, healthcare benefits and a fun highly social culture and environment. Our client would welcome someone who wants to come into a friendly outgoing Edinburgh office, but you could also do this remotely as long as you are free to live and work in the UK.
To apply to this role please contact our recruitment partner Bruce Hydes at GRw Talent
Machine Learning Engineer
Up to £70K DOE
Hybrid – London (2 days per week onsite)
My client is looking for a Junior to Mid-Level Machine Learning Engineer to take ownership of the infrastructure and services that power machine learning systems in production. In this role, you’ll act as a bridge between data science and engineering, ensuring robust, scalable, and low-latency deployment of models that serve millions of requests per day.
You’ll be responsible for building and maintaining Python microservices, leveraging modern DevOps practices and tooling to support rapid, reliable delivery. With sub-second response times and a high-throughput environment (2M+ requests/day), this is a high-impact role that blends software engineering, DevOps, and MLOps at scale.
Key Responsibilities
* Design, develop, and maintain Python microservices for serving machine learning models
* Collaborate with Data Scientists to deploy, monitor, and support models in production
* Implement and manage CI/CD pipelines using Azure DevOps
* Support containerized deployments with Kubernetes and Docker
* Ensure high performance, fault-tolerant, and secure infrastructure
* Promote code quality, testing standards, and scalable architecture
* Proactively identify infrastructure improvements and lead implementation
Requirements
* 2 + years of experience in Software Engineering, DevOps, or Data Engineering
* Strong Python skills with experience in microservices and web frameworks
* Solid understanding of CI/CD, ideally using Azure DevOps
* Familiarity with containerized environments (Docker/Kubernetes)
* Exposure to Data Science or Machine Learning concepts
* Experience operating in high-throughput environments
* Independent, curious, and driven by continuous improvement
* Effective communicator with the ability to bridge data science and engineering teams
Why Join?
You’ll be joining a company with strong business performance and ambitious plans for data-driven growth. This is a rare opportunity to take technical ownership of real-time machine learning infrastructure and play a key role in scaling systems that make an immediate business impact
01/06/2025
Machine Learning Engineer
Up to £70K DOE
Hybrid – London (2 days per week onsite)
My client is looking for a Junior to Mid-Level Machine Learning Engineer to take ownership of the infrastructure and services that power machine learning systems in production. In this role, you’ll act as a bridge between data science and engineering, ensuring robust, scalable, and low-latency deployment of models that serve millions of requests per day.
You’ll be responsible for building and maintaining Python microservices, leveraging modern DevOps practices and tooling to support rapid, reliable delivery. With sub-second response times and a high-throughput environment (2M+ requests/day), this is a high-impact role that blends software engineering, DevOps, and MLOps at scale.
Key Responsibilities
* Design, develop, and maintain Python microservices for serving machine learning models
* Collaborate with Data Scientists to deploy, monitor, and support models in production
* Implement and manage CI/CD pipelines using Azure DevOps
* Support containerized deployments with Kubernetes and Docker
* Ensure high performance, fault-tolerant, and secure infrastructure
* Promote code quality, testing standards, and scalable architecture
* Proactively identify infrastructure improvements and lead implementation
Requirements
* 2 + years of experience in Software Engineering, DevOps, or Data Engineering
* Strong Python skills with experience in microservices and web frameworks
* Solid understanding of CI/CD, ideally using Azure DevOps
* Familiarity with containerized environments (Docker/Kubernetes)
* Exposure to Data Science or Machine Learning concepts
* Experience operating in high-throughput environments
* Independent, curious, and driven by continuous improvement
* Effective communicator with the ability to bridge data science and engineering teams
Why Join?
You’ll be joining a company with strong business performance and ambitious plans for data-driven growth. This is a rare opportunity to take technical ownership of real-time machine learning infrastructure and play a key role in scaling systems that make an immediate business impact
We are Siemens Siemens DISWis a world-leading provider of product lifecycle management and manufacturingoperations management software. We help thousands of companies realiseinnovation by optimising their processes, from planning and development throughmanufacturing, production and support. Siemens DISW is a business unit of theSiemens Digital Industries Division. Driven by a deep understanding of what ittakes to deliver successful products. Help ourcustomers transform their business with our world-leading technology! TessentEmbedded Analytics is a pioneering developer of analytics and monitoringtechnology at the heart of the systems-on-chip (SoCs) that power today'selectronic products. Our embedded analytics technology allows product designersto add advanced cybersecurity, functional safety and performance tuningfeatures; and it helps resolve critical issues such as increasing systemcomplexity and ever- decreasing time-to-market. Requirements: Career background and/or education in technology (electronics, telecoms, manufacturing) with enough time in a practical data science role, but not forgetting the technology world: what we need and why Comfortable with deep learning and statistical learning methods and algorithms and familiarity with feature engineering Experience with using Python and relevant libraries (TensorFlow, Pandas, NumPy, scikit-learn, diagramming packages to name a few) Experience with C/C++ 11/14 , for implementing machine learning algorithms "on the edge" Understanding of data handling (databases, data storage, serialisation languages like XML, YAML) Experience with creating data visualisations Ability to understand complex products, solutions, and problems A real demonstrable desire to get things done and to advance both ours and our clients' businesses forward An understanding and interest in the world of silicon would be an advantage Ability to work independently including evaluating different solutions to a problem High level of proficiency and technical expertise; a curious and analytical approach Industrial experience: mid-level Responsibilities: Investigate and develop machine learning models working on data provided by Embedded Analytics hardware and other low-level sources close to the SoC; models will be applied in the areas of performance monitoring, cybersecurity, functional safety, anomaly detection (to name a few) Design models for deployment on the edge (embedded) or in the cloud or a combination of these Conceptualize, design, develop, modify, and implement machine learning applications and frameworks (both internal and external) Document the work being done (concepts, requirements, design) Work with software designs which may involve complicated workflows or multiple product areas Make sure the created source code conforms to coding standards (both internal and external) Ensure the functional quality of these applications on all required platforms Work with general supervision on complex projects with latitude for independent judgment At Siemens weare always challenging ourselves to build a better future. We need the mostinnovative and diverse Digital Minds to develop tomorrow's reality. Find outmore about the Digital world of Siemens here: Join our Digital World We are anequal opportunity employer and value diversity at our company. We do notdiscriminate on the basis of race, religion, colour, national origin, sex,gender, gender expression, sexual orientation, age, marital status, veteranstatus, or disability status. We offer acomprehensive reward package which includes a competitive basic salary, bonusscheme, generous holiday allowance, pension, private healthcare and activelysupport working from home. We willensure that individuals with disabilities are provided reasonable accommodationto participate in the job application or interview process, to perform crucialjob functions, and to receive other benefits and privileges of employment.Please contact us to request accommodation. At Siemens,we are always challenging ourselves to build a better future. We have some ofthe most inquisitive minds working across the world, re-imagining the futureand doing outstanding things. Join our Talent Community today and let's stayconnected in areas that interest you: Siemens Software. Where today meets tomorrow Organization: Digital Industries Company: Siemens Electronic Design Automation Ltd Experience Level: Experienced Professional Full / Part time: Full-time If you are a woman and cannot find jobs within engineering at Siemens that match your location or skill set why not join our talent community . While you're at it, why not set up job alerts to be notified of these fantastic opportunities when they become available!
23/09/2022
Full time
We are Siemens Siemens DISWis a world-leading provider of product lifecycle management and manufacturingoperations management software. We help thousands of companies realiseinnovation by optimising their processes, from planning and development throughmanufacturing, production and support. Siemens DISW is a business unit of theSiemens Digital Industries Division. Driven by a deep understanding of what ittakes to deliver successful products. Help ourcustomers transform their business with our world-leading technology! TessentEmbedded Analytics is a pioneering developer of analytics and monitoringtechnology at the heart of the systems-on-chip (SoCs) that power today'selectronic products. Our embedded analytics technology allows product designersto add advanced cybersecurity, functional safety and performance tuningfeatures; and it helps resolve critical issues such as increasing systemcomplexity and ever- decreasing time-to-market. Requirements: Career background and/or education in technology (electronics, telecoms, manufacturing) with enough time in a practical data science role, but not forgetting the technology world: what we need and why Comfortable with deep learning and statistical learning methods and algorithms and familiarity with feature engineering Experience with using Python and relevant libraries (TensorFlow, Pandas, NumPy, scikit-learn, diagramming packages to name a few) Experience with C/C++ 11/14 , for implementing machine learning algorithms "on the edge" Understanding of data handling (databases, data storage, serialisation languages like XML, YAML) Experience with creating data visualisations Ability to understand complex products, solutions, and problems A real demonstrable desire to get things done and to advance both ours and our clients' businesses forward An understanding and interest in the world of silicon would be an advantage Ability to work independently including evaluating different solutions to a problem High level of proficiency and technical expertise; a curious and analytical approach Industrial experience: mid-level Responsibilities: Investigate and develop machine learning models working on data provided by Embedded Analytics hardware and other low-level sources close to the SoC; models will be applied in the areas of performance monitoring, cybersecurity, functional safety, anomaly detection (to name a few) Design models for deployment on the edge (embedded) or in the cloud or a combination of these Conceptualize, design, develop, modify, and implement machine learning applications and frameworks (both internal and external) Document the work being done (concepts, requirements, design) Work with software designs which may involve complicated workflows or multiple product areas Make sure the created source code conforms to coding standards (both internal and external) Ensure the functional quality of these applications on all required platforms Work with general supervision on complex projects with latitude for independent judgment At Siemens weare always challenging ourselves to build a better future. We need the mostinnovative and diverse Digital Minds to develop tomorrow's reality. Find outmore about the Digital world of Siemens here: Join our Digital World We are anequal opportunity employer and value diversity at our company. We do notdiscriminate on the basis of race, religion, colour, national origin, sex,gender, gender expression, sexual orientation, age, marital status, veteranstatus, or disability status. We offer acomprehensive reward package which includes a competitive basic salary, bonusscheme, generous holiday allowance, pension, private healthcare and activelysupport working from home. We willensure that individuals with disabilities are provided reasonable accommodationto participate in the job application or interview process, to perform crucialjob functions, and to receive other benefits and privileges of employment.Please contact us to request accommodation. At Siemens,we are always challenging ourselves to build a better future. We have some ofthe most inquisitive minds working across the world, re-imagining the futureand doing outstanding things. Join our Talent Community today and let's stayconnected in areas that interest you: Siemens Software. Where today meets tomorrow Organization: Digital Industries Company: Siemens Electronic Design Automation Ltd Experience Level: Experienced Professional Full / Part time: Full-time If you are a woman and cannot find jobs within engineering at Siemens that match your location or skill set why not join our talent community . While you're at it, why not set up job alerts to be notified of these fantastic opportunities when they become available!
Robert Half have an exciting opportunity with a fast growing technology company in search of a MLOps Engineer to work alongside an established product and data team on creating robust frameworks and deploy machine learning models into production. My client is offering a great reward package, including: £60,000 to £80,000 experience dependant Remote working (offices in London and Edinburgh) Flexible working Annual success sharing bonus scheme No restriction on holiday allowance, trusted to manage workload and time Rewards scheme, pension scheme, cycle to work and much more The role includes: Sagemaker machine learning development pipelines Implementing monitoring and alerting for production model performance and accuracy Model optimization Deliver reusable software and modelling artefacts Continuous model training and deployment Collaborate with product managers, data scientists and engineering teams to integrate machine learning capabilities within the wider product offering The ideal candidate will have: Bachelor's degree or equivalent practical experience. Industry experience with machine learning pipelines Experience with kubernetes is a desirable Experience with one or more of Hive, Kafka, Impala or HDFS is also a desirable Working knowledge of AWS (Sage maker or cloudformation is desired) Proficiency with python and experience with ML frameworks such as PyTorch and TensorFlow The ability to forge strong relationships with clients and team members. Prove ability to deliver end-to-end solutions If you feel this role is for you, please apply and I'll be in touch with you in due course. Robert Half Ltd acts as an employment business for temporary positions and an employment agency for permanent positions. Robert Half is committed to equal opportunity and diversity. Suitable candidates with equivalent qualifications and more or less experience can apply. Where rates of pay or salary ranges are detailed these are dependent upon your experience, qualifications or training. If you wish to apply for this position please read our Privacy Notice which details how we may use, process, store and disclose your Personal Information: roberthalf.co.uk/privacy notice.
05/11/2021
Full time
Robert Half have an exciting opportunity with a fast growing technology company in search of a MLOps Engineer to work alongside an established product and data team on creating robust frameworks and deploy machine learning models into production. My client is offering a great reward package, including: £60,000 to £80,000 experience dependant Remote working (offices in London and Edinburgh) Flexible working Annual success sharing bonus scheme No restriction on holiday allowance, trusted to manage workload and time Rewards scheme, pension scheme, cycle to work and much more The role includes: Sagemaker machine learning development pipelines Implementing monitoring and alerting for production model performance and accuracy Model optimization Deliver reusable software and modelling artefacts Continuous model training and deployment Collaborate with product managers, data scientists and engineering teams to integrate machine learning capabilities within the wider product offering The ideal candidate will have: Bachelor's degree or equivalent practical experience. Industry experience with machine learning pipelines Experience with kubernetes is a desirable Experience with one or more of Hive, Kafka, Impala or HDFS is also a desirable Working knowledge of AWS (Sage maker or cloudformation is desired) Proficiency with python and experience with ML frameworks such as PyTorch and TensorFlow The ability to forge strong relationships with clients and team members. Prove ability to deliver end-to-end solutions If you feel this role is for you, please apply and I'll be in touch with you in due course. Robert Half Ltd acts as an employment business for temporary positions and an employment agency for permanent positions. Robert Half is committed to equal opportunity and diversity. Suitable candidates with equivalent qualifications and more or less experience can apply. Where rates of pay or salary ranges are detailed these are dependent upon your experience, qualifications or training. If you wish to apply for this position please read our Privacy Notice which details how we may use, process, store and disclose your Personal Information: roberthalf.co.uk/privacy notice.
Interesting Computer Vision use cases for global clients. A fast-growing company working with state-of-the-art innovative technology. Great time to join this rapidly growing team. I am currently working with a very exciting start-up here in Bristol who are looking for a Machine Learning Engineer to join their growing team and help support the development of their products and drive their ML capabilit...... click apply for full job details
17/03/2021
Full time
Interesting Computer Vision use cases for global clients. A fast-growing company working with state-of-the-art innovative technology. Great time to join this rapidly growing team. I am currently working with a very exciting start-up here in Bristol who are looking for a Machine Learning Engineer to join their growing team and help support the development of their products and drive their ML capabilit...... click apply for full job details
