551 to 575 of 612 MLOps Jobs in England

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 ...

TL;DR: We're looking for a Data Labeling Lead to build our annotation team from zero – setting quality standards, designing evaluation frameworks, and running the labeling operations behind our safety evals, RLHF, and benchmarks. ...

At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections, where you are valued, accepted and respected for who you ...

Radiant is redefining AI infrastructure with a senior/principal Product Manager - MLOps who owns strategy, roadmap, and delivery of the ML platform and cloud services. You will collaborate across GPU compute, training, inference, orchestration, model lifecycle, tooling, observability, and platform integrations with engineering, SRE, security, commercial teams, and customers. ...

operate AI infrastructure for enterprise AI workloads. You’ll work across hybrid and multi-cloud environments, delivering GPU-accelerated compute, model serving, and MLOps tooling while guiding clients through transformations. You will lead architecture reviews, workshops, and implementation of observability, security, and governance frameworks for AI systems. #J-18808-Ljbffr ...

Recruitment Limited is partnering with a leading organisation on a high-profile AI initiative to recruit an experienced MLOps/Platform Engineer. You will design, deploy, and operate a secure, scalable platform for AI workloads and agents, working closely with Data Science and Engineering teams to ensure robust infrastructure ...

powering forecasting solutions, working with data scientists and platform partners to productionize models and maintain high-availability production systems. You will design and operate MLOps pipelines, deployment workflows, and runtime infrastructure across cloud environments, aiming for performance, scalability, and cost efficiency. #J-18808-Ljbffr ...

owning deployment, monitoring and retraining, and building reusable components on the semantic layer. You will work with Data Scientists and Data Engineers to shape MLOps practices, implement CI/CD pipelines, monitor data drift, and optimize cost and performance of the model estate in a hybrid London office environment. #J ...

Junior DevOps/MLOps Engineer We are looking for a Junior DevOps/MLOps Engineer to help build, automate and maintain the infrastructure and pipelines that deliver software and machine learning models into production. Working alongside software and AI engineers, you will support reliable deployments, improve automation and help ensure ...

technologies that businesses can use to automate tasks and gain insights from their data. Key responsibilities include building complex models, designing and managing MLOps pipelines for CI/CD, monitoring, and model retraining. Mentoring junior members, influencing technical decisions within the team, and handling complex, non-routine problems. Our work … deploy complex machine learning models, ensuring high standards of quality, performance, and scalabilityDecide what model is most suitable for use in products and services MLOps Pipeline Management: Design and manage robust MLOps pipelines, including continuous integration/continuous delivery (CI/CD), monitoring, and model retraining, to ensure efficient ...

technologies that businesses can use to automate tasks and gain insights from their data. Key responsibilities include building complex models, designing and managing MLOps pipelines for CI/CD, monitoring, and model retraining. Mentoring junior members, influencing technical decisions within the team, and handling complex, non-routine problems. Our work … deploy complex machine learning models, ensuring high standards of quality, performance, and scalabilityDecide what model is most suitable for use in products and services MLOps Pipeline Management: Design and manage robust MLOps pipelines, including continuous integration/continuous delivery (CI/CD), monitoring, and model retraining, to ensure efficient ...

CoreWeave is seeking an experienced MLOps Engineer to own the end-to-end ML lifecycle—experimentation, training, packaging, deployment, serving, and retirement. You will define MLOps practices, establish SLOs/SLAs, and build automated CI/CD and continuous training pipelines for production readiness. You will implement observability, data/ ...

work across the full ML lifecycle, from experimentation and development through to deployment, monitoring and optimisation in production. You’ll help establish robust MLOps practices and ensure Machine Learning services are scalable, reliable and performant. There will also be a strong focus on performance and optimisation, including improving Python workloads … with frameworks Experience building and deploying Machine Learning models in production Experience working with Generative AI and modern Machine Learning technologies Strong understanding of MLOps, CI/CD and model deployment Experience building APIs for Machine Learning If you’re a Senior Machine Learning Engineer who enjoys taking sophisticated Machine ...

will develop, test, deploy, and enhance platform capabilities, resolve issues within existing analytics services, and provide hands-on engineering support to Data Scientists and MLOps teams working across a range of technologies. You will operate in a dynamic environment with varied and sometimes unfamiliar technical challenges, requiring strong problem-solving … lifecycle. Design, develop, test, and deployment of a new analytic hosting platform. Bugfixes and feature requests for existing mission facing analytics. Engineering support to MLOps engineers and Data Scientists. These are unpredictable and highly variable requirements, potentially using unfamiliar technology, so a flexible style is required. In this role ...