101 to 125 of 336 MLOps Jobs in the UK

Engineer and ML Engineer through to Senior, Lead, Applied Scientist and Research Engineer positions—for upcoming roles across applied machine learning, generative AI, MLOps and model productionisation. These are hands-on engineering roles where you'll build, train, ship and operate the models that drive real product behaviour and real … models at scale LLM and generative AI tooling exposure (LangChain, LlamaIndex, vector databases such as Pinecone, Weaviate or pgvector, RAG patterns, fine-tuning workflows) MLOps platforms (MLflow, Kubeflow, Vertex AI, SageMaker, Databricks or equivalent) Cloud experience (AWS, GCP, Azure), containerisation and basic data engineering/SQL Familiarity with experimentation ...

into enterprise platforms Collaborating closely with business stakeholders to translate requirements into scalable AI solutions Driving best practice across AI governance, model monitoring and MLOps Evaluating emerging AI technologies and identifying opportunities for innovation Skills & Experience We're looking for candidates with experience across several of the following: Commercial experience … learn Experience with Generative AI technologies including LLMs, LangChain or LlamaIndex Hands-on experience building RAG solutions and working with vector databases Experience with MLOps, CI/CD and containerisation Strong SQL skills and experience working with large datasets Cloud experience across Azure, AWS or GCP Excellent communication skills with ...

architectures and tool invocation frameworks Experience with CCaaS platforms (Google CES/CXAS, Genesys, NICE, Amazon Connect) Strong understanding of AI/ML lifecycle, MLOps, and data governance Experience working with Tier-1 banks or large financial institutions Certifications Google Cloud Professional Data Engineer (Highly Preferred) Google Professional Cloud Architect ...

Experience: Strong commercial understanding of the modern AI ecosystem, including: Generative AI Large Language Models (LLMs) Prompt Engineering Retrieval-Augmented Generation (RAG) Vector Databases MLOps Experience leading the implementation of enterprise-scale AI solutions and being accountable for delivery outcomes. Knowledge of cloud platforms such as AWS, Azure ...

Experience: Strong commercial understanding of the modern AI ecosystem, including: Generative AI Large Language Models (LLMs) Prompt Engineering Retrieval-Augmented Generation (RAG) Vector Databases MLOps Experience leading the implementation of enterprise-scale AI solutions and being accountable for delivery outcomes. Knowledge of cloud platforms such as AWS, Azure ...

platforms: Microsoft Azure (Fabric, Synapse, ADLS), AWS (Redshift, Glue, Lake Formation), GCP (BigQuery, Dataproc, Dataplex). Strong working knowledge of AI/ML engineering, MLOps, LLMOps, Generative AI, and Agentic AI frameworks. Familiarity with data governance tooling: Unity Catalog, Alation, Collibra, Purview, Snowflake governance, or equivalent. Ability to review, challenge ...

Mathematics Computer Science or a related quantitative discipline Desirable Skills for the Data Scientist: Experience with deep learning frameworks advanced modelling techniques Familiarity with MLOps concepts model monitoring deployment pipelines Exposure to tools such as Databricks MLflow feature stores Experience working in Agile product-led delivery environments Understanding of data ...

delivered through POSIT/RStudio. Key deliverables: Design a consolidated analytics and data science platform on Databricks. Enable notebook-based development, data science experimentation, MLOps, API integrations, and application deployment. Support external data ingestion, scheduling, BI connectivity, developer tooling, and operational reporting. Enable AI and LLM integration patterns. Develop migration ...

integration (APIs, microservices, messaging) and distributed systems Hands‐on experience with Microsoft Power Platform and low-code automation ecosystems Solid understanding of ML, GenAI, MLOps and DevOps practices A track record of influencing stakeholders and shaping technical strategy in complex environments The ability to simplify the complex and communicate with ...

growth over the last few years and we’re looking to continue with this momentum as we build on our reputation as Open Source MLOps experts, expand our role within the community, and continue to deliver high-quality solutions to our clients. What we’re looking for The ideal candidate … knack for creative problem solving. As well as being a great engineer, motivated by the chance to be at the forefront of MLOps adoption, you’ll also enjoy being part of a culture that values: Loving what we do: a real passion for Open Source, MLOps, and taking pride ...

impact. Experience with agentic telemetry, evaluation services, and orchestration of NLQ workflows. Demonstrated leadership working with engineers, data scientists, and AI practitioners. Familiarity with MLOps practices and AI pipelines. Hands‐on experience building and maintaining user interfaces for NLQ and data exploration. EEO Statement We recognize that our people ...

impact. Experience with agentic telemetry, evaluation services, and orchestration of NLQ workflows. Demonstrated leadership working with engineers, data scientists, and AI practitioners. Familiarity with MLOps practices and AI pipelines. Hands‐on experience building and maintaining user interfaces for NLQ and data exploration. We recognize that our people are our strength ...

techniques to power systems analysis, curtailment modelling, constraint analysis and renewable energy optimisation. Prototype and deploy AI solutions using cloud technologies and modern MLOps practices where appropriate. Produce clear visualisations and technical insights for planning applications, investment decisions and stakeholder reporting. Continuously evaluate emerging AI technologies and identify opportunities ...

modern AI technologies and concepts, including: Generative AI Large Language Models (LLMs) Prompt Engineering Retrieval-Augmented Generation (RAG) Vector Databases AI Solution Architecture MLOps Principles AI Governance and Risk Considerations Candidates are not expected to be hands-on developers but should be capable of guiding technical teams and contributing ...

approaches Agent-based architectures A practical understanding of how to apply LLMs to real-world use cases Tools & Engineering Experience with model deployment and MLOps tools (e.g. Databricks, MLflow) Familiarity with version control (Git) and collaborative development practices Awareness of best practices in code quality and reproducibility Communication & Consulting Ability ...

that support machine learning, advanced analytics or data products. You understand the full path from data quality and governance through to pipelines, model development, MLOps and production adoption. You can work credibly with senior product, commercial and engineering leaders. You’re comfortable making trade-offs across architecture, cost, delivery pace ...

that support machine learning, advanced analytics or data products. You understand the full path from data quality and governance through to pipelines, model development, MLOps and production adoption. You can work credibly with senior product, commercial and engineering leaders. You’re comfortable making trade-offs across architecture, cost, delivery pace ...

Large Language Models (LLMs) with proprietary OT data, maintenance manuals, and historian logs for intelligent operator assistance and automated root-cause analysis. Edge AI & MLOps: Operationalize lightweight machine learning models as containerized Azure IoT Edge modules to execute real-time anomaly detection, predictive maintenance, and closed-loop control tasks directly ...

customers. Our worldwide field engineering team applies expert insights to real‐world customer problems, enabling the enterprise adoption of Ubuntu, OpenStack, Kubernetes, AI/MLOps and a wide range of associated technologies. We are experts in the whole open source stack, from kernel to desktop, from cloud to the edge. ...

generation, environment design, mid-training, supervised fine-tuning, offline reinforcement learning, online reinforcement learning, reward modelling, transition modelling, etc. Our team also has dedicated MLOps, Infra and Inference support at scale. We focus on improving the long horizon, goal-conditioned instruction-following of large models for GUI/Computer ...

delivers.* You enjoy working collaboratively with Product Owners, Engineers, Analysts and business stakeholders to solve meaningful problems.* Experience with cloud-based Machine Learning platforms, MLOps, LLMs or Agentic AI is advantageous, although we're more interested in your ability to learn quickly and apply new technologies to solve business problems. ...

Belt. Experience building process digital twins and always-on conformance/monitoring capabilities. Familiarity with GenAI/LLMs, NLP, CV, RAG, knowledge graphs, and MLOps/LLMOps, and how they reshape process design. Knowledge of emerging regulatory expectations for AI in regulated industries. Risk, monitoring, bias/fairness, and incident ...

organisations solve complex operational, technical and regulatory challenges through AI adoption at scale. You will work across multidisciplinary teams, collaborating with data scientists, architects, MLOps/LLMOps engineers, business stakeholders and senior leadership to design, deliver and scale AI products, agentic AI solutions and data driven applications. Key responsibilities: Building … Using Python and SQL to build robust, scalable AI and data solutions Working with cloud platforms such as AWS, Azure, GCP or Databricks Supporting MLOps, LLMOps, CI/CD and software engineering best practice Collaborating with technical and non-technical stakeholders across complex programmes Helping identify technical, delivery, security, data ...

organisations solve complex operational, technical and regulatory challenges through AI adoption at scale. You will work across multidisciplinary teams, collaborating with data scientists, architects, MLOps/LLMOps engineers, business stakeholders and senior leadership to design, deliver and scale AI products, agentic AI solutions and data driven applications. Key responsibilities: Building … Using Python and SQL to build robust, scalable AI and data solutions Working with cloud platforms such as AWS, Azure, GCP or Databricks Supporting MLOps, LLMOps, CI/CD and software engineering best practice Collaborating with technical and non-technical stakeholders across complex programmes Helping identify technical, delivery, security, data ...

organisations solve complex operational, technical and regulatory challenges through AI adoption at scale. You will work across multidisciplinary teams, collaborating with data scientists, architects, MLOps/LLMOps engineers, business stakeholders and senior leadership to design, deliver and scale AI products, agentic AI solutions and data driven applications. Key responsibilities: Building … Using Python and SQL to build robust, scalable AI and data solutions Working with cloud platforms such as AWS, Azure, GCP or Databricks Supporting MLOps, LLMOps, CI/CD and software engineering best practice Collaborating with technical and non-technical stakeholders across complex programmes Helping identify technical, delivery, security, data ...