76 to 100 of 417 MLOps Jobs in the UK

that drives engagement, conversion, and growth. Oversee the design, training, and deployment of search and recommendation models — from data strategy to monitoring and performance optimisation. Collaborate with platform and MLOps teams to ensure robust, efficient, and scalable ML workflows (including CI/CD, feature management, and monitoring). Share insights and best practices across other ML teams, particularly in areas More ❯

that drives engagement, conversion, and growth. Oversee the design, training, and deployment of search and recommendation models — from data strategy to monitoring and performance optimisation. Collaborate with platform and MLOps teams to ensure robust, efficient, and scalable ML workflows (including CI/CD, feature management, and monitoring). Share insights and best practices across other ML teams, particularly in areas More ❯

that drives engagement, conversion, and growth. Oversee the design, training, and deployment of search and recommendation models — from data strategy to monitoring and performance optimisation. Collaborate with platform and MLOps teams to ensure robust, efficient, and scalable ML workflows (including CI/CD, feature management, and monitoring). Share insights and best practices across other ML teams, particularly in areas More ❯

that drives engagement, conversion, and growth. Oversee the design, training, and deployment of search and recommendation models — from data strategy to monitoring and performance optimisation. Collaborate with platform and MLOps teams to ensure robust, efficient, and scalable ML workflows (including CI/CD, feature management, and monitoring). Share insights and best practices across other ML teams, particularly in areas More ❯

years in a people leadership role. Expertise in AI, machine learning, deep learning, and predictive analytics. Strong proficiency in AI frameworks, cloud AI platforms (AWS, GCP, Azure), and MLOps practices. Solid understanding of AI ethics, governance, and compliance in a corporate setting. Proven track record of leading AI teams and managing AI projects. Strong strategic thinking, problem solving, and data More ❯

MLOps Engineer Outside IR35 - 500-600 Per Day Ideally, 1 day per week/fortnight in the office, flexibility for remote work for the right candidate. A market-leading global e-commerce client is urgently seeking a Senior MLOps Lead to establish and drive operational excellence within their largest, most established data function (60+ engineers). This is a mission … critical role focused on scaling their core on-site advertising platform from daily batch processing to real-time capability. This role suits a hands-on MLOps expert who is capable of implementing new standards, automating deployment lifecycles, and mentoring a large engineering team on best practices. What you'll be doing: MLOps Strategy & Implementation: Design and deploy end-to-end … MLOps processes, focusing heavily on governance, reproducibility, and automation. Real-Time Pipeline Build: Architect and implement solutions to transition high-volume model serving (10M+ customers, 1.2M+ product variants) to real-time performance. MLflow & Databricks Mastery: Lead the optimal integration and use of MLflow for model registry, experiment tracking, and deployment within the Databricks platform. DevOps for ML: Build and automate More ❯

Qualifications • 6–10 years of experience in applied data science, machine learning, or analytics leadership. • Strong understanding of model lifecycle management, experimentation frameworks, and data science governance. • Familiarity with MLOps concepts and tooling (e.g., MLflow, Kubeflow, Vertex AI, SageMaker, Azure ML). • Hands-on experience with data science tools and languages such as Python, R, SQL, and relevant frameworks (e.g. More ❯

Qualifications • 6–10 years of experience in applied data science, machine learning, or analytics leadership. • Strong understanding of model lifecycle management, experimentation frameworks, and data science governance. • Familiarity with MLOps concepts and tooling (e.g., MLflow, Kubeflow, Vertex AI, SageMaker, Azure ML). • Hands-on experience with data science tools and languages such as Python, R, SQL, and relevant frameworks (e.g. More ❯

Qualifications: • 6+ years of experience in applied data science, machine learning, or analytics leadership. • Strong understanding of model lifecycle management, experimentation frameworks, and data science governance. • Familiarity with MLOps concepts and tooling (e.g., MLflow, Kubeflow, Vertex AI, SageMaker, Azure ML). • Hands-on experience with data science tools and languages such as Python, R, SQL, and relevant frameworks (e.g., scikit More ❯

delivering AI/ML or automation projects end-to-end Strong skills in Python and modern ML/NLP/LLM techniques Experience with cloud, CI/CD, and MLOps workflows Ability to explain complex concepts clearly to varied audiences Experience with Databricks, Azure or AWS preferable More ❯

clean code, scalability, and technical excellence Nice to Have Experience with RAG systems, multi-agent AI, or Langfuse/LiteLLM Python proficiency for AI/ML integration Familiarity with MLOps and cost optimisation for AI systems Background in B2B SaaS or financial software More ❯

etc.) ☁️ Familiarity with cloud platforms (GCP preferred, or AWS/Azure) 🔍 Strong analytical mindset and ability to solve complex problems 🤝 Excellent communication and collaboration skills ⚙️ Experience with data engineering, MLOps, or automation tools is a plus Why Join Us? 🌍 Work with global teams across Europe 📈 Huge opportunity to grow in a major digital transformation environment 🤖 Build cutting-edge AI solutions More ❯

etc.) ☁️ Familiarity with cloud platforms (GCP preferred, or AWS/Azure) 🔍 Strong analytical mindset and ability to solve complex problems 🤝 Excellent communication and collaboration skills ⚙️ Experience with data engineering, MLOps, or automation tools is a plus Why Join Us? 🌍 Work with global teams across Europe 📈 Huge opportunity to grow in a major digital transformation environment 🤖 Build cutting-edge AI solutions More ❯

Proficient in Python and Linux/Unix environments. Nice to Have: Experience working across Sales, Product, and Engineering functions. Exposure to high-growth tech environments. Background in Data Engineering, MLOps, or cloud technologies (AWS, GCP, Azure, Kubernetes). More ❯

agile delivery approach, consistently documenting designs and results for leadership. Experience and Expertise Required We are looking for hands-on experience in the following core areas: Model Lifecycle Management (MLOps): Proven experience in implementing robust AI/ML pipelines for model training, validation, and deployment (e.g., using MLflow, Vertex AI, or Azure ML). Expertise in managing model evaluation, drift More ❯

agile delivery approach, consistently documenting designs and results for leadership. Experience and Expertise Required We are looking for hands-on experience in the following core areas: Model Lifecycle Management (MLOps): Proven experience in implementing robust AI/ML pipelines for model training, validation, and deployment (e.g., using MLflow, Vertex AI, or Azure ML). Expertise in managing model evaluation, drift More ❯

the following fundamental AI technologies: vector search, embedding models, recommender systems, supervised, unsupervised machine learning, deep learning, reinforcement learning, LLM orchestration, RAG systems, etc Familiarity with cloud services and MLOps tooling to deploy and scale data and ML workloads cost-effectively Familiarity with data warehouses (Redshift, BigQuery, Snowflake, etc) and best practices around data pipeline tools Strong proficiency in SQL More ❯

high-growth AI-driven fintech 🧠 Deep Technical Work: Opportunity to work on challenging, high-impact AI problems with real financial data and users 🛠 Modern Engineering Practices: Exposure to modern MLOps, experimentation workflows, and best practices in production AI 🤝 Collaborative Culture: Join a supportive, intellectually rigorous team that values deep thinking, ownership, and high-quality engineering ✨ Additional Perks: Pension scheme, private More ❯

high-growth AI-driven fintech 🧠 Deep Technical Work: Opportunity to work on challenging, high-impact AI problems with real financial data and users 🛠 Modern Engineering Practices: Exposure to modern MLOps, experimentation workflows, and best practices in production AI 🤝 Collaborative Culture: Join a supportive, intellectually rigorous team that values deep thinking, ownership, and high-quality engineering ✨ Additional Perks: Pension scheme, private More ❯

MLOps Engineer Outside IR35 - 500-600 Per Day Ideally, 1 day per week/fortnight in the office, flexibility for remote work for the right candidate. A market-leading global e-commerce client is urgently seeking a Senior MLOps Lead to establish and drive operational excellence within their largest, most established data function (60+ engineers). This is a mission … critical role focused on scaling their core on-site advertising platform from daily batch processing to real-time capability. This role suits a hands-on MLOps expert who is capable of implementing new standards, automating deployment lifecycles, and mentoring a large engineering team on best practices. What you'll be doing: MLOps Strategy & Implementation: Design and deploy end-to-end … MLOps processes, focusing heavily on governance, reproducibility, and automation. Real-Time Pipeline Build: Architect and implement solutions to transition high-volume model serving (10M+ customers, 1.2M+ product variants) to real-time performance. MLflow & Databricks Mastery: Lead the optimal integration and use of MLflow for model registry, experiment tracking, and deployment within the Databricks platform. DevOps for ML: Build and automate More ❯

experience developing ML models, with a strong focus on medical imaging Proven track record using deep learning frameworks (PyTorch/TensorFlow) Solid Python skills and familiarity with cloud or MLOps tools (Docker, Kubernetes, MLFlow) Understanding of data pipelines and image analysis techniques (segmentation, registration, feature extraction) Benefits Share options and private healthcare Flexible hybrid working 28 days’ holiday + bank More ❯

Excellent communication and cross-functional collaboration skills Nice to have Experience with vector databases , RAG systems , or multi-agent AI Python skills for AI/ML development Familiarity with MLOps , Langfuse , or LiteLLM Background in fintech , SaaS , or payments software Join a forward-thinking fintech where you’ll have the freedom to innovate, influence technical direction, and build AI systems More ❯

technical delivery. Desirable Skills Background in full-stack or backend engineering, using technologies such as Python, TypeScript, or .NET. Experience with data engineering and data architecture concepts. Familiarity with MLOps practices and AI development frameworks (e.g., Azure AI, LangChain, Hugging Face). Relevant certifications in Azure Architecture, Data, or AI disciplines. Knowledge of automation tools, monitoring, and observability platforms. If More ❯

Job Title: ML Engineer (AI) Location: London (Hybrid – 3 days in office) Industry: Media, Campaign Media, AI/Data Tech: Python, Data engineering, ML pipelines, MLOps, Model deployment Salary: £60-75k + shares *Unfortunately, Visa sponsorship is not on offer for this position. About the Role We’re hiring an AI Data Engineer to help build the next generation More ❯

Job Title: ML Engineer (AI) Location: London (Hybrid – 3 days in office) Industry: Media, Campaign Media, AI/Data Tech: Python, Data engineering, ML pipelines, MLOps, Model deployment Salary: £60-75k + shares *Unfortunately, Visa sponsorship is not on offer for this position. About the Role We’re hiring an AI Data Engineer to help build the next generation More ❯