526 to 550 of 598 MLOps Jobs in England

Senior Solutions Architect, Data & AI, AGS UKI Data & AI Solutions Architecture Job ID: 10581665 | AWS EMEA SARL (UK Branch) Amazon Web Services (AWS) is seeking an experienced Senior Solutions Architect to join our Data & AI ...

LEGO Group is seeking a Senior MLOps Engineer for a 16‐month parental cover in London. You will drive production deployment, monitoring, and reliability of customer-focused ML solutions, working with data science, data engineering and software engineering teams. You’ll help evolve our ML operations framework, align deployment decisions ...

EPAM Systems, Inc. in London is seeking an MLOps Engineer to build, deploy and maintain production-ready ML solutions with strong CI/CD and cloud infrastructure focus. You will work on ML lifecycle tooling, model serving, monitoring and extend capabilities toward LLMOps, RAG and agentic AI workflows. You will ...

Checkatrade is hiring an MLOps Engineer to own how ML/AI run in production. You will turn data scientists' models into live, reliable services and build secure foundations for AI workloads. Reporting to Head of Data Engineering, London (hybrid) or Barcelona (on-site). You will deploy, monitor ...

About the Job you are considering:We are seeking experienced Cloud MLOps Engineer Databricks Specialist with strong expertise in Banking domain who will overseeing the planning, execution, and successful delivery of projectsHybrid working:The places that you work from day to day will vary according to your role, your needs … sites, and your home; noting that you will be unable to work at home 100% of the time.Your Role:Purpose Implement ML workloads and MLOps capabilities on the Global AI PlatformConfigure and optimise Databricksbased ML development and deployment frameworksImplement model training deployment monitoring and governance capabilitiesAdapt or develop frameworks required ...

Halfords is seeking a Machine Learning Engineer to turn models into production-grade services powering customer and operational experiences. You will bridge software engineering, MLOps, and data science to build scalable pipelines and APIs deployed at enterprise scale. You will work with Data Scientists to move experiments into robust solutions ...

Machine Learning Engineer to turn ML models into production-grade solutions across the business. You’ll work at the intersection of software engineering, MLOps and data science, building frameworks, pipelines and services for deployment, monitoring and scaling of models from experimentation to live environments. You’ll partner with data scientists ...

build and deploy production-grade ML solutions, spanning the full ML lifecycle from experimentation to deployment and monitoring. The role focuses on Generative AI, MLOps, and scalable production systems, with emphasis on performance optimisation and close collaboration with software engineering and AI teams. #J-18808-Ljbffr ...

solutions. You will work with data scientists and engineers across the full lifecycle from data prep to production monitoring. The role emphasises scalable MLOps, governance, and collaboration with clients to deliver measurable outcomes. The position offers a hybrid working model with opportunities for professional development and participation in cutting-edge ...

knowledge-graph retrieval, partnering with product, data science, and Responsible AI teams to deliver scalable, governed systems using cloud platforms and industry-standard MLOps tools. #J-18808-Ljbffr ...

MLOps Engineer (Platform/DevOps) - AI Platform - 3 days per week onsite We're partnering with a leading organisation on a high-profile AI initiative, seeking an experienced MLOps/Platform Engineer to build and scale infrastructure supporting advanced AI solutions. The Role You'll play a key role ...

customer interactions into production-ready machine learning models that deliver more relevant, personalised experiences. Then make it real. About the role As our Senior MLOps Engineer, you’ll bring machine learning models out of the workshop and into dependable production environments during this 16-month parental cover. You’ll make ...

Capgemini is seeking an experienced Cloud MLOps Engineer Databricks Specialist to lead ML workloads and MLOps on the Global AI Platform. You will configure Databricks-based development and deployment frameworks, implement model training, deployment monitoring and governance, and build CI/CD pipelines for ML lifecycle management. You will drive ...

role in designing, building, testing and evolving scalable analytics hosting platforms, while also providing hands-on engineering support to Data Scientists and MLOps teams. The role offers plenty of variety, with the opportunity to work across a broad range of technologies and tackle complex technical challenges. You'll need … across existing analytics services. Deliver bug fixes and feature enhancements for mission-facing analytics platforms. Provide hands-on engineering support to Data Scientists and MLOps teams. Work across a varied technology landscape, adapting to unfamiliar technologies where required. Contribute to the design and implementation of reliable, scalable and secure technical ...

reliable production use. Working as part of our Enterprise AI team, you'll sit at the intersection of DevOps, cloud engineering, AI and MLOps , helping us create the technical foundations that allow AI solutions to be deployed effectively across the organisation. This is a great opportunity for someone with … capabilities across cloud and hybrid environments, giving you the opportunity to work with a broad range of technologies while developing expertise in AI platforms, MLOps and responsible AI delivery . What you will be doing Configuring and maintaining secure, scalable environments and services for AI workloads. Building repeatable deployment processes ...

workflows. You optimize the computational stack for performance, cost, power, and scalability, monitor AI systems and infrastructure health across both InfraOps and MLOps disciplines, perform AI monitoring to track model and system performance, and independently troubleshoot and resolve complex issues across the stack. You also mentor junior engineers, contribute … driven role where you apply and deepen your expertise across modern tools and platforms — including container orchestration, model serving, CI/CD pipelines, InfraOps, MLOps, and AI monitoring — while making meaningful contributions to infrastructure that enables AI-driven business outcomes. THE WORK Write, review, and debug code, scripts, and infrastructure ...

implementation and delivery. Provide technical governance and oversight across multiple AI initiatives. Define approaches for prompting, RAG, fine-tuning, evaluation, and AI guardrails. Establish MLOps and LLMOps capabilities to ensure solutions are scalable, observable, secure, and production-ready. Create architectural standards, reusable frameworks, and best practices across the AI practice. … Large Language Models, agent frameworks, orchestration patterns, and API-driven architectures. Strong cloud platform and modern software engineering experience. Hands-on expertise in MLOps/LLMOps, including deployment automation, monitoring, evaluation, and optimisation. Strong Python development skills and the ability to prototype and validate technical approaches. Experience balancing multiple projects ...

supporting AI/ML workloads. You'll apply deep technical expertise across infrastructure automation, environment provisioning and deployment pipelines , working closely with Data Engineers, MLOps Engineers and Solution Architects to ensure the platform meets performance, scalability, cost and compliance requirements. There is flexibility on base location across … Vault and Azure AD Supporting connectivity between on-prem services and Azure cloud infrastructure (hybrid networking/private connectivity, including GreenLink) Working with MLOps and Data Engineers to ensure environments are reproducible, reliable and auditable across multiple environments Supporting observability and platform health: logging and metrics monitoring using tooling such ...

data science projects from discovery through to production deployment. Analyse and prepare large datasets from operational, asset, weather and market sources. Build and maintain MLOps pipelines to support reliable and scalable model deployment. Create dashboards, visualisations and applications that communicate insights to stakeholders. Work closely with engineers, operators and business … Strong Python programming skills, including experience with libraries such as pandas and scikit-learn. Experience designing, deploying and maintaining machine learning solutions using modern MLOps practices. Experience extracting, manipulating and analysing data using SQL. Ability to communicate complex technical concepts clearly to both technical and non-technical stakeholders. Degree ...

enterprise sales cycles and co‐own the technical win Lead deep technical discovery sessions with a wide range of stakeholders (from ML Engineers to MLOps leaders) to not only uncover business pain but to architect a complete technical solution and integration path Architect, build, and deliver highly‐technical, customised product … delivery in a complex enterprise sales environment Proven track record of earning trust with highly technical audiences (ML engineers, MLOps, data engineers) while communicating value clearly to senior business stakeholders Experience navigating enterprise security, compliance, and architecture reviews as part of a technical sales or implementation process Prior experience ...

accuracy, and consistency of training data across multiple concurrent projects and robot platforms. Collaborate with machine learning teams to shape the Capability Factory, streamline MLOps, and build the evaluation workflows that close the loop between training runs and real-world robot performance. Build data warehouse solutions and BI dashboards that … been on-call, triaged incidents under pressure, and improved systems after postmortems. You take reliability personally. Nice to Have ML infrastructure or MLOps experience - understanding of how training jobs run, how model artifacts are managed, and what makes an evaluation pipeline trustworthy; you\'ve worked alongside or directly supported ...

discovery, consulting and solution conversations from initial opportunity through to delivery. AI engineering excellence. Setting high standards across architecture, engineering, testing, CI/CD, MLOps/LLMOps, evaluation, security and AI governance. Production AI. Ensuring solutions move beyond experimentation into reliable, scalable and governed production environments. Solution design. Challenging architecture … prototype through to reliable production use. Strong software engineering fundamentals including system design, APIs, version control, automated testing and CI/CD. Experience of MLOps/LLMOps and operating AI systems in production. Experience with modern cloud AI technologies and platforms. Led engineers building AI systems while retaining strong technical ...

successful, production‐scale machine learning solutions (ideally on AWS SageMaker). You will provide technical leadership across ML lifecycle, including defining architecture, engineering standards, MLOps practices, and governance frameworks for a large‐scale matching platform. This is a hands‐on lead role requiring recent expertise in building, deploying, monitoring … Establishing engineering standards and operational excellence. Implementing feature stores, Lakehouse architectures, and enterprise data quality frameworks. Coaching engineers, reviewing designs, and driving technical direction. MLOps, Deployment & Operations Deep hands‐on experience with SageMaker Pipelines, Training, Processing, Model Registry, Endpoints, Monitoring, and deployment workflows. CI/CD, infrastructure as code, model ...

reliable, well-monitored, cost-effective models in production - deployment, retraining, monitoring and governance - and the service levels (SLAs) of the ML organization. Partnering with MLOps infrastructure team. Partner across the company. Translate commercial strategy into an ML roadmap with Product, Engineering, Design, and Analytics leadership; represent ML in executive planning … across Product and Engineering and shaping strategy, not just execution. A strategic player-coach's technical depth: current enough in modern ML, experimentation, and MLOps to set direction, review architecture, and hold the scientific bar. Strong grounding in experimentation and statistics — A/B testing, causal inference, and rigorous measurement ...

We're one of Europe's fastest-growing fintech companies – on a mission to create the world's most empowering way to pay. We launched the product in 2020 and achieved double unicorn status, valued ...