69 jobs for “mlops”
Databricks London
Customer-facing engineering role building and productionizing data and AI solutions on the Databricks platform for emerging enterprise and digital native accounts. You own architecture and design decisions, implement end-to-end systems spanning data engineering, ML/AI and application development, and embed with client teams. Billable delivery work with roughly 20% travel.
Databricks London
Customer-facing engineering role owning architecture and design decisions while building production-grade data, AI and application systems on the Databricks platform. You embed with client teams, from technical ICs to executives, to scope and deliver end-to-end solutions, contributing reusable accelerators and product feedback. Requires hands-on coding in Python, Scala or TypeScript, deep Apache Spark and distributed computing expertise, and multi-cloud knowledge, with around 20% travel to customer sites.
McGregor Boyall London £115,000 pa
Hands-on role designing, developing and deploying production-grade Generative AI and Agentic AI solutions within a global technology consultancy's Data & AI practice. Combines Data Science and Machine Learning foundations with modern software engineering, including Python APIs, microservices, RAG architectures, vector databases and MLOps, while influencing solution architecture and working directly with clients on AI transformation projects.
Rise Technical Recruitment London £90,000 – £120,000 pa
Design and build full-stack AI-powered product features, working across front-end, back-end, AI and infrastructure. Develop and optimise LLM, computer vision and agent-based systems, plus evaluation, prompt engineering and fine-tuning frameworks. High-ownership role shaping product direction and AI strategy in a scaling financial crime prevention start-up.
Morson Edge West Yorkshire £170,000 – £180,000 pa
A senior leadership role owning the data and AI strategy, roadmap and technical direction across the organisation. Day to day it spans hands-on work with generative AI, LLMs, RAG and agentic architectures, MLOps and data platform governance, plus building and leading a high-performing Data & AI team and partnering with Product, Engineering, Architecture and Security to scale prototypes into production.
Harnham - Data and Analytics Recruitment London £120,000 – £150,000 pa
Lead and build a data science function within a fintech, owning strategy across risk, affordability and lending decisioning. Design, build and deploy machine learning models using credit risk, Open Banking and customer data, working with Product, Engineering and Credit Risk teams. Requires hands-on Python, SQL and MLOps experience plus credit risk modelling in UK consumer lending.
University of Bristol Bristol £44,746 – £50,253 pa
Builds and operates the software-defined compute and storage/networking platforms behind the UK's most powerful supercomputer, using Python, Rust, Terraform/OpenTofu, Kubernetes, Git and Bash. Works closely with AI researchers to co-design and debug massive-scale GPU and CPU/GPU workloads, with a focus on stability, security and scaling.
Ricoh London
Builds, configures and operates the platforms and services that take enterprise AI solutions from evaluation into secure, scalable production. Works across DevOps, cloud engineering and MLOps with AI specialists, data scientists and security teams, covering CI/CD, automation, monitoring, secrets management and cost optimisation in cloud and hybrid environments.
Pure Resourcing Solutions Cambridge £80,000 – £100,000 pa
Provisioning and running multi-rack GPU clusters for training and inference at a not-for-profit AI organisation, covering hardware, fabric and orchestration. The role spans high-performance networking (InfiniBand, RDMA, RoCE), advanced Linux across Ubuntu and RHEL, virtualisation, and infrastructure-as-code with Git and Terraform/OpenTofu, working closely with researchers and engineers.
Scale AI United Kingdom
Fellows join an interdisciplinary expert network and are matched to short-term AI/ML projects, ranging from evaluating models and designing experiments to building RL environments and reviewing PyTorch code. They may also co-author technical reports and research papers with Scale's research team. Engagement is fully remote, self-scheduled, with no minimum commitment.
Opus Recruitment Solutions United Kingdom £80,000 – £90,000 pa
Designs enterprise-scale AI, data and automation solutions, architecting generative and agentic AI, RAG, vector database and multi-agent systems across OpenAI, Azure OpenAI, Anthropic and Google Gemini. Runs customer discovery and solution-design workshops, creates reference architectures and roadmaps, and supports technical pre-sales, governance and Responsible AI. Remote-first with client site visits.
AECOM London
Lead the design and deployment of applied machine learning models for infrastructure and engineering, owning the full lifecycle from problem formulation to production iteration. Work spans optimisation, simulation and scientific ML, partnering with MLOps, software and domain experts to embed AI into a SaaS platform, with mentoring and technical leadership duties.
CONVENTUS SOLUTIONS LIMITED Cyprus
Bridges research and production engineering, deploying and testing computer vision and ML systems for object tracking, automated monitoring and intelligent triaging in live environments. Involves turning research models into production-grade software, running specialised data collections and labelling, and briefing senior leadership on capability. Requires expert Python, Docker, Kubernetes and active DV clearance.
Relation Therapeutics London
Join the Platform Team to design and scale Kubernetes-based hybrid compute clusters across private and public clouds, building core platform services and APIs. You will own CI/CD pipelines, monitoring, backup and disaster recovery, and work closely with Machine Learning and Data Science teams to support their computational needs.
PhysicsX San Francisco, United States US$150,000 – US$190,000 pa
Builds and deploys machine learning pipelines for industrial physics applications, working directly with customers on-site to embed AI models into practical tools. Involves manipulating 3D point-cloud and mesh data, cloud and HPC infrastructure, and translating R&D outputs into reusable libraries and products.
