1 to 25 of 111 Remote MLOps Jobs in London

LLM orchestration frameworks, and prompt tuning. Familiarity with RAG pipelines, embedding models, and vector databases. Experience with cloud platforms (AWS, GCP, Azure) and AI/ML services. Knowledge of MLOps tools and practices (e.g., MLflow, Kubeflow, Vertex AI, Azure ML). Strong understanding of data engineering, data pipelines, and ETL workflows. Excellent problem-solving, communication, and stakeholder engagement skills. Bachelor More ❯

LLM orchestration frameworks, and prompt tuning. Familiarity with RAG pipelines, embedding models, and vector databases. Experience with cloud platforms (AWS, GCP, Azure) and AI/ML services. Knowledge of MLOps tools and practices (e.g., MLflow, Kubeflow, Vertex AI, Azure ML). Strong understanding of data engineering, data pipelines, and ETL workflows. Excellent problem-solving, communication, and stakeholder engagement skills. Bachelor More ❯

real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from SQL to large-scale distributed data tools (Spark, etc.). Strong written and verbal communication skills, especially More ❯

real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from SQL to large-scale distributed data tools (Spark, etc.). Strong written and verbal communication skills, especially More ❯

algorithms based on project requirements. Evaluate models using appropriate metrics and perform hyperparameter tuning for optimal performance. Convert proof-of-concept models into production-grade pipelines in collaboration with MLOps and engineering teams. Required: Translate model outcomes into actionable insights through clear storytelling and visualizations. Build dashboards and reports using Power BI, Tableau, or Python-based visualization tools. Communicate findings More ❯

pragmatic mindset — able to balance innovation with execution. ✨ Nice-to-haves: Experience leading platform or DevOps product teams in life sciences, research, or AI-driven organisations . Familiarity with MLOps, GenAI, and large-scale compute orchestration . Background in computer science, engineering, or a related technical discipline. 💰 Package & Benefits: Base salary up to £145,000 . Car allowance , 18% bonus More ❯

pragmatic mindset — able to balance innovation with execution. ✨ Nice-to-haves: Experience leading platform or DevOps product teams in life sciences, research, or AI-driven organisations . Familiarity with MLOps, GenAI, and large-scale compute orchestration . Background in computer science, engineering, or a related technical discipline. 💰 Package & Benefits: Base salary up to £145,000 . Car allowance , 18% bonus More ❯

pragmatic mindset - able to balance innovation with execution. Nice-to-haves: Experience leading platform or DevOps product teams in life sciences, research, or AI-driven organisations . Familiarity with MLOps, GenAI, and large-scale compute orchestration . Background in computer science, engineering, or a related technical discipline. Package & Benefits: Base salary up to £145,000 . Car allowance , 18% bonus More ❯

Career Growth: Direct mentorship from senior AI engineers and founders, clear progression in a high-growth AI compliance company 🛠 Modern Tech Stack on AWS: Work with cutting-edge LLMs, MLOps tooling, Python, TypeScript, and an AWS-native cloud stack 🤝 Collaborative Culture: Join a supportive, mission-driven team passionate about safe and responsible AI ✨ Additional Perks: Pension scheme, private healthcare, regular More ❯

Career Growth: Direct mentorship from senior AI engineers and founders, clear progression in a high-growth AI compliance company 🛠 Modern Tech Stack on AWS: Work with cutting-edge LLMs, MLOps tooling, Python, TypeScript, and an AWS-native cloud stack 🤝 Collaborative Culture: Join a supportive, mission-driven team passionate about safe and responsible AI ✨ Additional Perks: Pension scheme, private healthcare, regular More ❯

based data platforms (AWS, Azure, or GCP). Proven track record in credit risk modelling, fraud analytics, or similar financial domains. Familiarity with big data technologies (Spark, Hive) and MLOps practices for production-scale deployments. Excellent communication skills to engage stakeholders and simplify complex concepts. Desirable Extras Experience with regulatory frameworks (e.g., Basel, GDPR) and model explainability tools. Knowledge of More ❯

based data platforms (AWS, Azure, or GCP). Proven track record in credit risk modelling, fraud analytics, or similar financial domains. Familiarity with big data technologies (Spark, Hive) and MLOps practices for production-scale deployments. Excellent communication skills to engage stakeholders and simplify complex concepts. Desirable Extras Experience with regulatory frameworks (e.g., Basel, GDPR) and model explainability tools. Knowledge of 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 ❯

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 ❯

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 ❯

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 ❯

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 ❯