126 to 150 of 336 MLOps Jobs in the UK

learning frameworks, and Generative AI/LLM components. Pipelines: Develop and optimize Retrieval-Augmented Generation (RAG) pipelines, vector databases, and scalable data processing streams. MLOps: Implement model deployment, monitoring, testing, and lifecycle management using standard CI/CD and containerized workflows. Architecture: Contribute to technical design decisions, trade-off analyses … Azure, or GCP) using Docker and Kubernetes. Engineering: Strong software engineering fundamentals, including version control, testing, and API/microservices architecture. Experience with MLOps platforms (e.g., MLflow, SageMaker) or agentic AI frameworks. Familiarity with secure development practices or regulated/high-compliance environments. Background in NLP, computer vision, or data ...

systems into complex banking and capital markets environments Establish and govern evaluation frameworks for AI and agent-based systems Oversee CI/CD, MLOps, and LLMOps practices across delivery teams Work closely with security, risk, and compliance teams to ensure ethical and regulated AI delivery Own and contribute to architecture … similar) Strong understanding of evaluation frameworks for AI/agent systems Experience implementing CI/CD pipelines and modern engineering practices Exposure to MLOps/LLMOps principles Experience working with at least one cloud hyperscaler (AWS, Azure, GCP, or Databricks) Strong Agile delivery experience (Agile, SAFe, XP, Jira, Confluence, etc. ...

deployment models across enterprise environments Advising clients on suitable AI use cases and opportunities for enterprise-wide adoption Collaborating with Enterprise Architects, Data Scientists, MLOps Engineers, DevOps teams and business stakeholders to shape and deliver solutions Selecting and implementing appropriate cloud, open-source and commercial AI technologies Leading the delivery … hosting Retrieval Augmented Generation (RAG), vector databases, semantic search and embedding techniques Python development and AI frameworks such as PyTorch, TensorFlow and LangChain MLOps frameworks and AI model lifecycle management API integration and enterprise-wide AI solution delivery Presenting architecture solutions to senior stakeholders, governance forums and architecture boards ...

applications. You’ll drive end-to-end development from discovery to production, work across voice, vision, and text, and leverage LangChain, LlamaIndex, and modern MLOps on AWS/Azure/GCP to deliver scalable, observable AI solutions at scale. #J-18808-Ljbffr ...

Azure Machine Learning. Define data platform architecture, analytics pipelines, and enterprise integration patterns. Collaborate with engineering teams to implement CI/CD and MLOps best practices. Provide technical leadership, governance, and architectural guidance to stakeholders and delivery teams. Essential Skills Strong enterprise architecture experience across AWS, Azure, and hybrid/ ...

translate complex business problems into data modelling and decisioning solutions Strong understanding of modern data science tooling and ecosystems such as Python R SQL MLOps and Databricks Commercial awareness with the ability to identify and shape high value use cases Excellent stakeholder engagement skills including working with senior ...

environments Nice to Have Hands-on experience building LLM or agentic AI applications Experience with frameworks such as LangGraph, RAG or MCP Understanding of MLOps and AI deployment practices Experience testing and evaluating non-deterministic AI systems Infrastructure as Code and cloud platform experience, ideally AWS Why Join? Competitive salary ...

Experience with agent frameworks, tool-use planning and workflow orchestration Systems-level fluency across data pipelines, training infrastructure and inference (PyTorch, JAX, TensorFlow) Strong MLOps discipline: CI/CD for models, offline/online evaluation, safety and guardrails The ability to influence at exec level and mentor senior technical talent ...

modelling experience Experience working with large datasets and technologies such as PySpark or Hive Familiarity with version control systems such as Git Understanding of MLOps principles and production deployment practices Exposure to containerisation technologies such as Docker Experience with Kubernetes or workflow orchestration tools Why Join Us? This ...

Semantic Kernel Power Platform Enterprise Data Platforms Azure Machine Learning Retrieval-Augmented Generation (RAG) Large Language Models (LLMs) Agentic AI architectures LangChain/LangGraph MLOps & LLMOps Cloud-native architectures Data governance and security frameworks What We're Looking For You'll likely be operating as an AI Architect, Lead ...

engineering excellence across the team. Partner with sales and tech leadership to define requirements for high‐value opportunities, deploying specialized experts (Machine Learning Operations (MLOps), Generative Media (GenMedia), or Agentic systems) to key accounts. Lead technical hiring for FDE, evaluating AI/ML expertise, systems engineering, and coding skills ...

AI. Build POVs and architecture options that balance business value, feasibility, and cost. Act as a trusted advisor for our clients across data platforms, MLOps, Generative and Agentic AI, and application design. Thought Leadership, GTM & Vertical Expertise Represent Datatonic on site at client, at events, conferences, partner sessions, and executive ...

quantitative discipline, e.g. Computer Science, Mathematics, Statistics Track record of developing, deploying business critical machine learning models Broad knowledge of MLOps tooling – for versioning, reproducibility, observability etc Experience monitoring, maintaining, enhancing existing models over an extended time period Specialism in NLP or Computer Vision Solid understanding of fundamentals of statistics ...

technical or business field. Bonus qualifications: Experience with AI accelerators or GPUs LLM fine-tuning or inference knowledge Familiarity with Sambanova products or similar MLOps platforms Enterprise SaaS or PaaS background MBA or advanced technical degree Base Salary Range: £94,500 - £115,000 GBP #J-18808-Ljbffr ...

integration challenges of deploying AI within regulated market systems.* Strong command of modern AI capabilities: LLMs, agentic frameworks, RAG, ML inference, and MLOps, sufficient to lead technical teams and challenge engineering decisions.* Demonstrated ability to drive AI adoption at scale, navigating organisational complexity, change management, and business stakeholder alignment.* Exceptional ...

partner with the commercial leadership to deliver high-value AI-driven opportunities that enhance efficiency, customer experience, and growth. Establish best practices for MLOps, experimentation, model monitoring, and continuous optimisation. Data Engineering & Architecture Oversee the design and delivery of scalable, secure, and modern data platforms, pipelines, and architectures. Ensure data ...

entire spectrum of cloud offerings, from Ubuntu itself to virtualisation and private cloud, Kubernetes, and the implementation of sophisticated open source solutions such as MLops platforms, data platforms and more. We are rapidly expanding the range of open source solutions we offer and deliver to customers, as we move into ...

technical or business field. Bonus qualifications Experience with AI accelerators or GPUs LLM fine‐tuning or inference knowledge Familiarity with Sambanova products or similar MLOps platforms Enterprise SaaS or PaaS background MBA or advanced technical degree Base Salary Range £94,500—£115,000 GBP Benefits Summary SambaNova offers a competitive ...

technical delivery while also leading multiple projects or workstreams in parallel. Desirable • Experience establishing or embedding best practice in ML engineering, software delivery or MLOps within a team or function. • Experience in regulated, enterprise or operationally complex environments. • Experience promoting reuse through shared frameworks, tooling, templates or engineering standards. • Experience ...

delivery of AI projects end to end from the silicon and data center design that underpins AI workloads, through the software and MLOps stack, to the governance frameworks that make AI trustworthy and defensible at scale. This is a technical hardware-and-software architect role, not a strategy-only position. … parallel/high-throughput storage, and orchestration Design the AI software stack: training and fine-tuning pipelines, distributed training frameworks, inference/serving platforms, MLOps/LLMOps tooling, vector databases, and retrieval-augmented generation (RAG) and agentic architectures. Define and AI governance frameworks covering model risk management, responsible AI, data ...

hybrid in London, moving AI from prototype to production across cloud-native platforms. Responsibilities include AI solution design, cloud engineering on GCP, data, MLOps, Responsible AI governance, and collaboration with underwriters and operations. Strong Python and LLM experience required. #J-18808-Ljbffr ...

Perform feature engineering to improve model accuracy Design ML pipelines and automate model deployment Collaborate with software engineers to integrate models into applications Use MLOps practices for monitoring, retraining, and lifecycle management Conduct A/B tests and measure real-world model performance Stay up to date with the latest ...

major impact across product quality, infrastructure efficiency and technical direction. What we’re looking for 5+ years’ experience within Applied AI/ML/MLOps Strong Python and production AI systems experience Experience with LLMs, Generative AI, prompt engineering or agentic workflows Exposure to AI infrastructure, deployment, evals or optimisation ...

degree or equivalent experience. What Will Make You Stand Out: Experience delivering AI and automation initiatives that drive measurable business value. Knowledge of MLOps, AI governance and responsible AI frameworks. Experience building modern, scalable data platforms and architectures. A track record of leading organisational change through data and digital transformation. ...

optimisation). Experience leading or managing data scientists on impactful ML/optimisation projects. Excellent Python and SQL skills, with clean, maintainable code. Practical MLOps experience (deployment, monitoring, lifecycle management) in a cloud environment (AWS or similar). Comfortable working with large, imperfect datasets and making sound, pragmatic decisions. Familiarity ...