Job Title: Senior MLOps Engineer Company: RELX Group Job Category: Machine Learning Roles & Responsibilities: About the role: As a Senior MLOps Engineer, you should be able to define the scope of a project with support of managers and execute that project independently. Individuals in this role can also support the development and training of junior staff. Senior Data Scientist I should be self\-sufficient in executing basic methods, and work within their teams to execute increasingly sophisticated approaches to deliver outcomes. They should also support the development of best practices. Key Responsibilities: * Maintain and version model registries and artifact stores to ensure reproducibility and governance * Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. * Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. * Design and implement the engineering components of GAR\+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self\-hosted * Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs * Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization * Partner with Subject\-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions We promote a healthy work/life balance across the organization. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long\-term goals. A global leader in information and analytics, we help researchers and healthcare professionals’ advance science and improve health outcomes for the benefit of society. Building on our publishing heritage, we combine quality information and vast data sets with analytics to support visionary science and research, health education, and interactive learning, as well as exceptional healthcare and clinical practice. At Elsevier, your work contributes to the world’s grand challenges and a more sustainable future. We harness innovative technologies to support science and healthcare to partner for a better world. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1\-855\-833\-5120\. Work Location: London, ENG, UK Availability: Full time
Job Title: NSL- ML Engineer Company: BAE Systems Job Category: Machine Learning Roles & Responsibilities: Job Description As a Senior ML Engineer, you will design, develop, and iterate on machine learning models that support national security objectives. You will collaborate with Data Scientists, Software Engineers, Product Management and Government business stakeholders across the full lifecycle, from hypothesis through to production deployment. Leveraging our AWS\-based infrastructure you will apply modern MLOps/LLMOps tooling to run rigorous experiments, track results, and deliver scalable solutions. A key aspect to the role is to balance rapid experimentation with production readiness, prototyping and validating ML approaches while ensuring successful experiments integrate seamlessly into operational systems. This is an exciting time to join our team to help pioneer both our customer's and our own AI adoption journey. Not only will you be directly making a huge impact through the solutions you develop, you’ll be doing it for an organisation who makes a huge impact to the security of the UK. Core Duties * Design and develop machine learning models for traditional ML use cases (forecasting, classification, anomaly detection) and GenAI/LLM applications * Lead experimentation cycles: define hypotheses, design experiments, evaluate results, and iterate rapidly while adhering to governance requirements * Transition validated experiments into production\-ready solutions, working closely with other engineers on deployment and monitoring * Build and optimise ML pipelines using AWS services and experiment tracking tools * Develop and integrate LLM\-powered solutions for tracing, evaluation, and production monitoring * Implement robust experiment tracking, model versioning, and reproducibility practices with full audit trails * Design feature engineering approaches and contribute to feature store development * Support production models through monitoring, performance analysis, and continuous improvement * Apply responsible AI practices, including model explainability and fairness assessment * Present experiment findings and production outcomes to stakeholders, articulating operational and strategic value * Mentor junior colleagues and share learnings across the team * Hands\-on experience developing and deploying ML models in Python using frameworks such as scikit\-learn, XGBoost, PyTorch, or TensorFlow * Strong experience with AWS ML services (SageMaker, Lambda, S3\) in production environments * Strong experiment design skills: hypothesis formulation, A/B testing methodology, and statistical evaluation * Proven track record transitioning models from experimentation to production with appropriate governance and quality controls * Experience with experiment tracking and MLOps tooling (MLflow, Weights \& Biases, Data Version Control) * Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures * Familiarity with LLMOps tooling such as LangSmith, LangChain, or LangGraph * Understanding of model evaluation, validation techniques, and production monitoring * Experience working in cross\-functional teams from problem framing through to production delivery * Ability to communicate complex findings to non\-technical audiences clearly * Strong problem\-solving skills and knowing when AI is not the answer How we will support you --------------------------- * Work\-life balance is important; you can work around core hours with flexible and part\-time working * As many of our customers work predominantly in the office, we expect all of our staff to work at least 3 days per week in the office * You’ll get 25 days holiday a year and the option to buy/sell and carry over from the year before * Our flexible benefits package includes private medical and dental insurance, a competitive pension scheme, cycle to work scheme, taste cards and more * You’ll have a dedicated Career Manager to help you develop your career and guide you on your journey through BAE * You’ll be part of our company bonus scheme * You are welcome to join any/all of our Diversity and Support groups. These groups cover everything from gender diversity to mental health and wellbeing Work Location: London, ENG, UK Availability: Full time
Job Title: Senior Machine Learning Engineer Company: Houseful Job Category: Machine Learning Roles & Responsibilities: The Role We are looking for a Senior Machine Learning Engineer to bring intelligent automation and predictive capability to the heart of the UK property market. Alto sits at a unique intersection: we process an enormous volume of real transaction data, and we're only beginning to unlock what that means for the products our customers rely on every day. This is a role for someone who wants to build ML systems that genuinely change how people buy and sell homes — not maintain models that gather dust. What You'll Do * Design, build, and deploy end\-to\-end machine learning pipelines — from data ingestion and feature engineering through to model serving and monitoring in production * Own the full lifecycle of ML models: evaluate, iterate, and retire them with the same rigour you bring to building them * Collaborate closely with product and engineering teams to frame business problems as machine learning problems, and translate model outputs into product features users actually understand * Establish and maintain standards for ML reproducibility, experiment tracking, and model versioning across the Data team * Identify opportunities to apply ML across Alto's product suite — surfacing ideas proactively, not waiting to be briefed * Work with large, complex datasets drawn from live UK property transactions, ensuring data quality and feature reliability upstream of every model * Contribute to a culture of engineering excellence through code reviews, documentation, and knowledge\-sharing with data engineers and analysts Our Technology Stack * Backend: TypeScript, Node.js, C\#, .NET * Infrastructure: AWS (ECS, Lambda, SQS, DynamoDB), Terraform * Architecture: Microservices, Event\-driven architecture * Data \& ML: Python, AWS SageMaker, S3, Redshift Why Join Alto? This role gives you genuine ownership of ML capability at a company that processes more housing transactions than anyone else in the UK — the data advantage is real and largely untapped. You will have the scope to define how machine learning is built and deployed at Alto, not slot into a pre\-defined process. It's an exciting moment to join: we're investing seriously in our Data function, and this hire will shape its direction. We want to make Alto more welcoming, fair and representative every day. We'll consider everyone who applies for this role in the same way, regardless of your ethnicity, colour, national origin, religion, sexual orientation, gender, gender identity, age, physical disability, neurodiversity status, family or parental status, or how long you've spent unemployed. Work Location: London, England, UK Availability: Full time
Job Title: AI Engineer Company: Change Digital – Digital & Tech Recruitment Job Category: Machine Learning Roles & Responsibilities: This is an exciting opportunity to join a growing AI practice and work on cutting\-edge projects spanning Generative AI, LLMs, AI Agents, Machine Learning, and Data Science. The role offers genuine responsibility, exposure to client\-facing delivery, and a clear pathway to leadership. The Role As an AI Engineer, you'll play a key role in delivering AI\-powered solutions across a variety of client projects. You'll work with Large Language Models (LLMs), Retrieval\-Augmented Generation (RAG), AI Agents, and traditional machine learning techniques to solve real\-world business challenges. Working alongside senior AI and Data Science leaders, you'll own significant project workstreams, turning solution designs into robust, production\-ready software whilst helping to mentor junior colleagues and contribute to the growth of our AI practice. * Building, testing, and deploying AI and Machine Learning solutions * Developing GenAI applications using LLMs, RAG architectures, and agentic workflows * Delivering end\-to\-end data science activities including feature engineering, model training, and evaluation * Writing clean, maintainable, production\-focused Python code * Supporting model evaluation, monitoring, and optimisation * Collaborating with clients and project teams to deliver tangible business outcomes Work Location: Edinburgh, Scotland, UK Availability: Full time
Job Title: Machine Learning Engineer Company: Halfords Job Category: Machine Learning Roles & Responsibilities: Business Area: Halfords Support Centre About the role You'll work closely with Data Scientists to understand the problems they're solving and the models they're developing, helping transform experimental code into robust, maintainable, and secure production solutions. From building CI/CD pipelines and automated retraining processes to designing APIs, orchestration frameworks, and monitoring capabilities, you'll ensure machine learning solutions can operate reliably at enterprise scale. This is an exciting opportunity to join a growing data science function that has strong backing from senior leadership and a clear vision for the future. As Halfords continues its journey towards a more personalised and data\-driven customer experience, you'll play a key role in embedding machine learning into core business processes and customer journeys. If you enjoy solving complex engineering challenges and seeing your work underpin real\-world AI and machine learning applications, you'll have the opportunity to make a significant impact from day one. Key responsibilities * Partner with Data Scientists to transition models from experimentation into scalable, production\-ready applications and services * Design, build, and maintain MLOps frameworks, deployment pipelines, and automated model lifecycle processes * Develop and support CI/CD pipelines, version control frameworks, and automated testing processes for machine learning solutions * Build APIs, services, and integration patterns that enable machine learning models to be embedded into business systems and customer\-facing applications * Implement model monitoring, performance tracking, drift detection, and automated retraining capabilities to ensure ongoing reliability and business value * Work with cloud\-native technologies including Azure Databricks, MLflow, and related platforms to support enterprise\-scale machine learning workloads Collaborate with Data Engineers, Architects, and Developers to deliver secure, scalable, and maintainable machine learning solutions * * Proven experience deploying machine learning solutions into production environments and supporting them throughout their lifecycle * Strong understanding of version control practices, including Git, branching strategies, and release management * Strong software engineering skills in Python, with a solid understanding of engineering best practices, testing, code quality, and maintainability * Experience building CI/CD pipelines, MLOps frameworks, and automated machine learning deployment processes * Hands\-on experience with Azure Databricks or similar machine learning platforms (ie MLFlow, KubeFlow, SageMaker etc) * Experience building APIs, microservices, and cloud\-based solutions that integrate machine learning capabilities into wider platforms and applications Excellent collaboration and technical communication skills, with the ability to work effectively alongside Data Scientists, Architects, Engineers, and Business Analysts / Project Managers. * * A fair and competitive salary evaluated against market data, annual discretionary bonus scheme, pension, life assurance, 25 days annual leave plus bank holidays and enhanced family leave. * Commitment and dedication to your ongoing personal and professional development. We help you to own and grow your potential so you can be at your best in your current role and to support your future career aspirations. * We offer hybrid working with a blend of working in our Support Centre and from home. * You will have access to a wealth of employee discounts across the Halfords suite of products and services. * Wellbeing and inclusion are at the heart of our colleague experience. We offer resources and ongoing support to enhance your wellbeing at work and active Colleague Networks supporting inclusion initiatives across Halfords. Note: Halfords operates a hybrid working policy – this position will be based 3 days per week at our support centre in Redditch, West Midlands. Work Location: Redditch, ENG, UK Availability: Full time
Job Title: Senior Applied ML Engineer | Kimchi (Model Router) Company: CAST AI Job Category: Machine Learning Roles & Responsibilities: #### About the role * You've worked on LLM routing specifically: RouterBench\-class evals, cost/quality/latency Pareto fronts. * Calibration, abstention, or conformal methods in production decision systems. * You've run online A/B loops with drift monitoring on a model that touches real money. #### Responsibilities * Own the routing model end to end: features, objective, training, calibration, and release cadence. Iterate it like a product, not a research artifact. * Build the evaluation that gates every change: production\-parity benchmarks, router\-vs\-router comparisons, holdouts by task family, error bars on pass rates. Nothing ships on vibes. * Turn fleet data into training signal: per\-request outcomes from production, benchmark rollouts, and override feedback, with failure categorization (infra vs task) so poisoned labels never reach the policy. * Model the objective the user actually experiences: task success × token cost × wall\-clock speed under the real concurrency regime, with cached\-input economics in the picture. * Run the online loop: shadow, A/B, full rollout, drift monitoring, retrain. When production disagrees with your offline eval, you find out why before the next ship. * Push the frontier where it pays: calibrated decisions, abstention under uncertainty, speed\-aware routing. We experiment on what a router should be, not just which model it picks today. * Partner with platform engineers on instrumentation: the features and labels recorded per request (decode speed first\-class among them) and the experiments the data path must support. Work Location: Remote, UK Availability: Full time
Job Title: Senior Machine Learning Engineer Company: Prima Job Category: Machine Learning Roles & Responsibilities: You’ll be joining over 350 engineers across software development, infrastructure, operations and security. Fueled by curiosity, experimentation and collaboration, you’ll help deliver scalable, impactful solutions that shape the future of insurance. Excited to make an impact? Here are the details What You Will Do * Defining the model development methodologies and best practices, following the whole life cycle with a central role in choosing the technological stack; * Supporting the productionalization and evolution of the Oracles, entities that through machine learning pilot the behavior of Prima's microservices; * Developing the tools (packages, microservices, pipelines...) that you deem fundamental for your and your team job; * Growing, reading, and experimenting to always be up to speed with emerging technology. 🌈 Thrive and perform: Your best work begins when you feel your best. Enjoy private healthcare, gym discounts, wellbeing programs and mental health support. Work Location: London, England, UK Availability: Full time
Job Title: Senior Machine Learning Engineer Company: Epic Games Job Category: Machine Learning Roles & Responsibilities: Being Epic means being a part of a team that continually strives to do right by our community and users. We’re constantly innovating to raise the bar of engine and game development. What We Do Unreal projects have been leading the pack of real\-time entertainment with our constantly growing team of engineering experts. We’re always improving on the tools and technology that empower content developers worldwide. What You'll Do You will work with our team of applied research engineers at the intersection of computer vision, gameplay agents, natural language processing, and machine learning to create state\-of\-the\-art tools to support game developers in our ecosystem with a focus on bots (trained gameplay agents, intelligent NPCs, companions, world modeling), as well as automation of a number key areas (including moderation, security, and QA testing). You will be responsible for the design, implementation and deployment of production\-ready machine learning models that can be integrated in our ecosystem. In this role, you will * Create and deliver production\-ready, scalable and high\-quality machine learning models and associated algorithms that can make actions in game environments * Critically assess the effectiveness of such models and make recommendations for the ongoing roadmap * Methodically understand and assess the effectiveness of new data channels and support collection/creation of new ones About Us Epic Games is a leading interactive entertainment company. For over 30 years we've been making award\-winning games and engine technology that empowers others to make visually stunning games and 3D content that bring environments to life like never before. Epic's award\-winning Unreal Engine technology not only provides game developers the ability to build high\-fidelity, interactive experiences for PC, console, mobile, and VR, it is also a tool being embraced by content creators across a variety of industries such as media and entertainment, automotive, and architectural design. As we continue to build our Engine technology and develop remarkable games, we strive to build teams of world\-class talent. Work Location: Greater London, England, UK Availability: Full time
Job Title: Graduate Machine Learning Engineer Company: G-Research Job Category: Machine Learning Roles & Responsibilities: As part of our engineering team, you’ll shape the platforms and tools that drive high\-impact research \- designing systems that scale, accelerate discovery and support innovation across the firm. ### Role purpose ### Key Responsibilities of the role include * Implementing ideas from published research papers * Writing custom libraries to efficiently train models on petabytes of data * Reducing model training times by hand optimising machine learning operations * Profiling custom ML architectures to identify performance bottlenecks * Evaluating the latest hardware and software in the machine learning ecosystem Work Location: London, ENG, UK Availability: Full time
Job Title: Senior ML Engineer Company: CreateFuture Job Category: Machine Learning Roles & Responsibilities: CreateFuture is an AI\-native consulting partner where people do work that matters and are supported to do it well. We work alongside organisations such as PayPal, adidas, NatWest, FanDuel and Money Saving Expert, building digital products and services that make a difference while always putting people first. We're a team of creators. We write code, shape delivery, build go\-to\-market strategies, develop AI solutions and create the practices that support our people. We work side by side with our clients, challenging what's not working and helping them to build the future. Our commitment to craft, quality, and culture has helped us scale to over 600 people in just a few years. ### About the role and team: * Take ownership of designing, building, and maintaining the production data and feature pipelines that machine learning systems depend on, training data preparation, feature engineering, and reproducible, point\-in\-time\-correct datasets, with minimal supervision * Take models from prototype to production and keep them there: packaging and deployment alongside data science colleagues, model versioning, automated retraining, and the monitoring that catches drift and degradation before a client does * Build and maintain the batch and ELT pipelines the ML work sits on, using Python, PySpark, and cloud data services (e.g., AWS Glue, EMR, S3, Redshift, Athena, or the Databricks / Snowflake equivalents), making sound decisions on architecture, data modelling, and tooling and weighing up trade\-offs in performance, cost, and maintainability * Own and continuously improve CI/CD for data and ML workflows, ensuring reliable, repeatable deployments of pipelines and models alike * Mentor and support junior and mid\-level data engineers, reviewing code and sharing knowledge to raise the standard of delivery across the team * Troubleshoot and resolve complex issues in live data pipelines and deployed models, acting as a point of escalation for the wider team * Partner with data scientists, cross\-functional teams, and client stakeholders to understand data and ML requirements and shape them into technical solutions * Have hands\-on experience building the data and feature pipelines behind production machine learning, training data preparation, feature engineering, and feature stores, and understand why reproducibility and point\-in\-time correctness matter more than they first appear * Have worked with MLOps in practice rather than in principle: model versioning and registries, experiment tracking, automated retraining, and monitoring for drift and model degradation (MLflow, SageMaker, Databricks ML, Vertex AI or comparable) * Are comfortable with ML frameworks such as scikit\-learn, PySpark MLlib, or PyTorch / TensorFlow, enough to productionise a data scientist's work, reason about what a model needs from the data, and spot where a training pipeline and a serving pipeline have quietly diverged. You don't need to be the person designing the model * Have designed and operated production data pipelines on a modern cloud data platform, AWS (Glue, EMR, Redshift, S3/Lake Formation), Databricks, Snowflake or comparable, and can talk about which of those decisions would travel to a different one, and which wouldn't * Have deep SQL skills and hands\-on experience with data modelling (e.g., Kimball, medallion/lakehouse patterns, or domain\-driven modelling), this is the load\-bearing, provider\-agnostic skill underneath almost all of our pipeline work * Have strong Python and PySpark for batch processing, with production\-grade, well\-tested code. The bulk of this work is batch and ELT, but you'll need to have experienced event\-driven or micro\-batch pipelines and know where the design assumptions stop holding * Have owned orchestration in production, dependency design, retries, SLAs, and the observability that tells you a pipeline failed before the client does * Have experience owning the delivery of data engineering work with limited oversight, including CI/CD management and support * Have experience mentoring or supporting the development of less experienced engineers * Are comfortable working directly with stakeholders to shape technical solutions from ambiguous requirements, presenting your work, estimation and discussing tradeoffs and risks. ### What we'll offer you: We trust people to do their best work. That means flexibility over rigid rules, impact over activity, and real investment in your growth both professionally and personally. You'll be part of a supportive, and friendly culture, surrounded by smart, curious people who care deeply about what they do. We trust you to manage your time balancing collaboration with client time and focused work. What matters is the impact you have, not how busy you look. Depending on the role, we might also ask you to do a short presentation, a practical or technical task or have a values focused conversation. We will explain what is involved before anything happens. If you need any adjustments or support during the application process, just. We will do what we can to help. Work Location: Leeds, ENG, UK Availability: Full time
