51 to 75 of 90 MLOps Jobs in the UK excluding London

Confidence operating across multiple workstreams while building sustainable AI and analytics capability within teams Bonus Points For Hands-on experience with AI product development, MLOps, model lifecycle management or AI platform engineering Knowledge of responsible AI, model risk management, AI governance or ethical AI frameworks Experience supporting AI strategy, roadmap ...

architectures that seamlessly integrate AI/ML solutions with existing insurance systems. Collaborate with Enterprise, Application, Data & DevOps Architects, Data scientists, MLOps & GenAI Engineers, and Business teams to pilot use cases and discuss architectural design. Select appropriate technologies from a pool of open-source and commercial offerings, considering deployment models … writing robust and efficient code in Python. Experience in using tools relevant to deep learning like PyTorch, TensorFlow, LangChain. Experience in designing & implementing key MLOps capabilities & frameworks in delivering robust train, test, monitor and improve lifecycles for AI/ML model deployments. Experience in developing and integrating APIs especially related ...

cloud platforms and modern data architectures Proven ability to design and govern large-scale data and AI solutions Experience with CI/CD, MLOps and infrastructure-as-code approaches Confident communicator able to work with both technical and non-technical audiences Eligible for SC clearance (5+ years continuous UK residency ...

stay there Experience working in commercial environments where data drives decisions Strong Python (or R) experience across modern data science tooling Familiarity with MLOps, model monitoring, and deployment pipelines Ability to communicate complex outputs clearly to non-technical stakeholders ...

Synthetic Biology, Deep Tech, TechBio, Director of Engineering, ML Platform, AI Infrastructure, Lab Automation, Bioinformatics, Player-Coach, Engineering Leadership, AI Agents, LLMs, Python, Numpy, MLOps, Life Sciences AI, Biotechnology. ...

internal capability Bonus Points For Prior experience in business development or pre-sales within a consultancy environment Hands-on familiarity with modern data science, MLOps or AI operationalisation Knowledge of data ethics, AI governance or analytics operating models Change management or business analysis experience within large transformation programmes Confidence ...

clearly communicate to both technical and non‐technical audiences. Ability to work effectively in a cross‐functional team. Experience with model lifecycle management and MLOps, including model deployment, versioning and monitoring. Good knowledge of cloud services, ideally AWS. Knowledge and understanding of best practices such as testing, code management ...

inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. MLOps Engineer (SC Clearance) Position Description At CGI, you will play a pivotal role in enabling the deployment and operation of advanced AI systems that support critical … bringing innovative approaches to platform engineering while being supported by experienced colleagues and a collaborative culture focused on continuous improvement. •Design & Deliver secure, scalable MLOps platforms for production environments •Build & Optimise air-gapped machine learning pipelines and workflows •Deploy & Manage LLM inference clusters and AI model hosting platforms •Implement & Enhance ...

monthly billing Promotion to Consultant within 6 months based on performance Structured, hands-on training from experienced AI recruiters Strong market demand across GenAI, MLOps, and data science Year 1 OTE £40k, Year 2 £50k, Year 3 £65k Early exposure to founders and technical hiring managers Clear targets and transparent ...

infrastructure every pricing professional aspires to work with: · High-quality, accessible data · A fast, flexible rating algorithm — deploy changes in hours · Machine Learning Operations (MLOps) that enable fast, transparent, and controlled model development · An operating model that gives complete autonomy to pricing professionals to dream up an idea ...

infrastructure every pricing professional aspires to work with: · High-quality, accessible data · A fast, flexible rating algorithm — deploy changes in hours · Machine Learning Operations (MLOps) that enable fast, transparent, and controlled model development · An operating model that gives complete autonomy to pricing professionals to dream up an idea ...

securing data-related business opportunities Expertise across data domains: data strategy, data governance, data privacy, and analytics delivery Strong understanding of data science, AI, MLOps, BI tools, ethics in AI, and analytics operating models Proven ability to lead large-scale data transformation initiatives within Financial Services Bonus Points For Experience ...

Tune machine learning methods to best leverage our state-of-the-art processing capabilities Deploy and maintain machine learning methods in a DevOps/MLOps based machine learning environment Create robust high-quality code using test-driven development (TDD) techniques and adhering to the SOLID coding standards Your work will … Director of Technical Underwriting Propose, proof-of-concept, develop, and deliver novel machine learning processes that automate current manual processes, and leverage DevOps and MLOps software. Work in a collaborative environment with data science to help deploy machine learning methods that are state-of-the-art, robust, and future extensible. ...

following predictive modelling techniques; GBMs, Elastic Net GLMs, GAMs, Logistic Regression, Random Forests, Decision Trees, Neural Nets and Clustering Experience in DevOps, or other MLOps and ML Lifecycle stacks Experience with Docker and Kubernetes Experience in creating production grade coding Experience in programming languages (eg Python, PySpark ...

Kantar can rely on , not just prototype with. You'll design and build the foundations that enable production‐grade AI: reusable GenAI components, strong MLOps practices, and cloud‐native services that balance quality, cost, and reliability. Your work will help teams move faster, avoid common pitfalls, and deliver AI solutions … including RAG, embeddings, semantic search, and agent‐based workflows Shaping how GenAI systems handle prompting, grounding, evaluation, reliability, and cost control Building and evolving MLOps pipelines , from experimentation through deployment, monitoring, and iteration Engineering cloud‐native, API‐driven services that integrate AI into production platforms Supporting and guiding other engineers ...

design, build and deploy advanced NLP and LLM-based solutions, taking models from research through to production. You’ll work closely with AI, data, MLOps and product teams to translate business and regulatory requirements into scalable, reliable AI systems. This is a hands-on role for someone who enjoys owning … data preprocessing pipelines Monitoring, optimising and maintaining deployed models for performance, cost and reliability Implementing explainability, fairness and bias-mitigation strategies Collaborating on MLOps pipelines, CI/CD workflows and production deployments Mentoring junior engineers and promoting best practices across the team Staying current with advances ...

This job is with Capgemini, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Data Science Senior Consultant/Senior ...

This job is with Capgemini, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Data Science Senior Consultant/Senior ...

LlamaIndex) & Agentic architectures (LangGraph, SmolAgents, PydanticAI) Vector DBs & RAG: Designed solutions using vector DBs & Retrieval Augmented GenAI (RAG) for knowledge applications. GenAI ModelOps/MLOps & Governance: GenAI ModelOps/MLOps knowledge with ethical AI governance focus. ER&I GenAI Applications: Applied GenAI to ER&I use cases to create business ...

LlamaIndex) & Agentic architectures (LangGraph, SmolAgents, PydanticAI) Vector DBs & RAG: Designed solutions using vector DBs & Retrieval Augmented GenAI (RAG) for knowledge applications. GenAI ModelOps/MLOps & Governance: GenAI ModelOps/MLOps knowledge with ethical AI governance focus. ER&I GenAI Applications: Applied GenAI to ER&I use cases to create business ...

LlamaIndex) & Agentic architectures (LangGraph, SmolAgents, PydanticAI) Vector DBs & RAG: Designed solutions using vector DBs & Retrieval Augmented GenAI (RAG) for knowledge applications. GenAI ModelOps/MLOps & Governance: GenAI ModelOps/MLOps knowledge with ethical AI governance focus. ER&I GenAI Applications: Applied GenAI to ER&I use cases to create business ...

practices across their ML and data setup, ensuring it is ready to support multiple enterprise deployments. Key responsibilities: * Audit current ML architecture, pipelines, and MLOps practices * Identify gaps in documentation, reproducibility, and scalability * Introduce clear structure across model development, versioning, and deployment * Improve training and retraining workflows * Strengthen model monitoring … Python and hands-on ML engineering experience * Proven experience in productionising ML systems end-to-end * Experience auditing and improving existing ML setups * Strong MLOps experience (model versioning, monitoring, CI/CD) * Experience working with data pipelines (ETL/ELT, Spark or similar) * Comfortable working with messy, real-world data ...

including LLM-based patterns such as embeddings, retrieval approaches, and model tuning where appropriate). [Principal_...ad_AI_0426 | Word] Setting engineering standards for MLOps: CI/CD, model deployment, monitoring, evaluation, and operational reliability. Architecting secure, cloud-native services (microservices, APIs, messaging/event-driven patterns) that support … needed Experience building, deploying, and maintaining machine learning and generative AI solutions (e.g., LLMs, embeddings, retrieval patterns, vector search, model fine‐tuning). Strong MLOps knowledge across continuous integration, deployment, monitoring, and evaluation of AI/ML models. Experience with AI infrastructure (orchestration pipelines, GPU compute, model hosting services ...

learning engineer, you will work with and under the expert supervision of machine learning engineers to help build and maintain the pricing team’s MLOps and ML Lifecycle environment and support the creation of pipelines by automating the sophisticated machine learning models and processes that underpin our market-leading technical … modelling and pricing function. Key Responsibilities: Build an MLOps/DevOps environment to support machine learning automation. Build the pipelines that automate the regular model update and monitoring processes. Work with the Technical Underwriting machine learning engineers to develop, implement, and maintain scalable and processes and codebase that facilitate efficient ...

preprocessing, augmentation, and validation workflows. Run structured experiments, evaluate model performance, and iterate based on measurable results Build, deploy, and operate end-to-end MLOps pipelines, including experiment tracking, model versioning, and production monitoring. Package and deploy models using Docker and cloud infrastructure, with a focus on reliability and scalability … familiarity with the Hugging Face ecosystem Experience with audio or speech models and frameworks. Experience building and maintaining end-to-end ML pipelines and MLOps tooling (e.g. MLflow, Weights & Biases, DVC, or similar). Strong Python skills; experience with Docker, CI/CD, and cloud platforms (Azure preferred) Practical experience ...