1 to 25 of 41 Remote MLOps Jobs in the City of 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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

stacks (TypeScript, Node.js, Go, or similar) Strong understanding of ML principles and model evaluation Experience with cloud-based model deployment (GCP preferred) Familiarity with containerised workflows (Docker, serverless) and MLOps tools (MLflow, Vertex AI, SageMaker) Excellent communication and collaboration skills in a remote-first team Willingness to travel occasionally for in-person collaboration or client work Nice to Have Experience More ❯

/CD, build/release pipelines, and automation Exposure to containers and orchestration (Docker, Kubernetes, ECS/AKS) Experience with monitoring/observability Interest in AI, ML pipelines, or MLOps (experience highly beneficial but not essential) Someone who enjoys ownership, autonomy and working in a small, smart engineering team Why it’s a great move High-impact role working directly More ❯

natural problem solver with curiosity for cutting-edge tools and frameworks Desirable Experience Experience delivering AI or ML solutions in a commercial or consultancy setting Knowledge of data engineering, MLOps, or automation workflows Previous experience engaging directly with clients and senior stakeholders Why Join This is an opportunity to join a fast-scaling AI business at a defining stage of More ❯

and ability to work cross-functionally. Desirable MSc/PhD in Machine Learning, Computer Vision, or related field. Knowledge of Generative AI models (GANs, diffusion, LLMs). Experience with MLOps and lifecycle management. Experience in startups or fast-paced R&D. Why apply? Flexible hybrid working (London office) A chance to shape the future of AI in sport and human More ❯

findings into actionable insights for coaches, analysts, and execs Highly Desirable Skills Football Analytics Experience : Familiarity with football-specific datasets (event, tracking, positiona l), and libraries like mplsoccer Advanced MLOps & Modelling : Experience with the Vertex AI ecosystem, especially pipelines, and advanced techniques such as player valuation , tactical modelling , etc. Bayesian Modelling : Knowledge of probabilistic programming (e.g., PyMC ) for uncertainty-aware More ❯

Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million Users | UK Remote OR London, Hybrid, 1 Day PW, Up to £140,000 About the Company Our client is an extremely well know, digital marketplace focused on sustainable ecommerce. With over 35 million of active users globally, they’re redefining how people buy and sell second-hand fashion, aiming to make the future … The organisation champions diversity, equal opportunity, and flexible working. They offer a progressive benefits package designed to support wellbeing, learning, and work-life balance. The role of Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million Users | UK Remote OR London, Hybrid, 1 Day PW, Up to £140,000 Our Client is looking for an experienced MLOps Engineering Manager to lead and … scale their MLOps function. You will be shaping how machine learning is developed, deployed, and scaled across the organisation. This is a genuinely high-impact role: you’ll lead a talented team of 6-8 engineers, set the strategic direction for ML infrastructure, and ensure the business continues to deliver reliable, scalable, and high-performing ML systems that drive real More ❯

with the flexibility for some work from home. The AI Engineer will support delivery of AI use cases, workflows, analytics and solutions - responsible for tasks such as pattern recognition, MLOps, software development, neural networks, and natural language processing on a day-to-day basis. Qualifications Pattern Recognition and Neural Networks skills Computer Science and Software Development skills Natural Language Processing More ❯

the machine learning strategy and direction for assigned projects. Lead the design, training and validation of models and algorithms. Maintain hands-on involvement. Work collaboratively with data engineers (note: MLOps responsibilities are handled by the engineering team). Contribute to broader AI and ML strategy development within the engagement. Required Skills & Experience 6+ years’ experience in Data Science. Demonstrated experience More ❯

bonus Principal: £120,000–£140,000 base + ~20%+ bonus Team : 3–4 person AI team within a 100-person private equity firm Tech Stack : Python, LLMs, MLOps, cloud (Azure, AWS, GCP), agentic systems Visa Sponsorship : Happy to sponsor Interested? Please apply below. More ❯

Senior Data Scientists/Analysts – SC/DV Cleared – (Military/Veteran-Friendly) — Multiple Openings 🌳 Location: London (Remote & Hybrid options) 🌳 Employment: Permanent 🌳 Clearance: Current SC or DV required 🌳 Make sense of mission-critical data that actually drives decisions. 🌳 Areti Group More ❯

to drive AI/ML innovation while ensuring models are scalable and impactful. What You’ll Be Doing: Developing predictive models to forecast property trends and customer behavior. Leveraging MLOps best practices to ensure efficient model deployment and monitoring. Working end-to-end across the data pipeline – from data extraction to model evaluation. Collaborating with cross-functional teams to turn More ❯

can translate technical topics into business outcomes Experience supporting B2B SaaS or AI/ML platform customers 💡 Bonus Points For: Experience with generative models (e.g., diffusion, transformers) Knowledge of MLOps or model serving Fluency in French, German, Italian, or Dutch 🌟 Why Apply? Join one of the most innovative AI teams in Europe Shape the future of ethical Generative AI adoption More ❯

benefits Industry: Technology Scale Up, circa 300 people The role: You will lead the design & development of robust Machine Learning models to solve complex problems. You will work alongside MLOps to help build the ML infrastructure for these models to be deployed, and then maintain & scale these efficiently. You will continuously collaborate across internal stakeholders to ensure the models being More ❯

defined library for initial deployment (e.g., finance or operational materials) Basic access controls, validation and testing Skills & Experience Strong proficiency in Python with experience in machine learning deployment and MLOps tooling Understanding of SharePoint. Strong Azure, or similar cloud-based storage and directory structures Experience building document or knowledge management systems Ability to work autonomously, taking ownership from design through More ❯

for ML developments within a scaleup environment. What you’ll do: Architect and build scalable ML systems in GCP and AWS Drive end-to-end delivery across experimentation, modelling, MLOps and deployment Set technical direction, mentor teams, and champion best practices Work closely with product and data teams to turn ideas into real-world impact Collaborate with 3rd party vendors More ❯

stories, change requests, and screen designs. A background as a Business Analyst is preferred. Experience in workforce management, scheduling, HR tech, optimisation domains, AI/ML productisation, LLM integration, MLOps, or enterprise integration standards (ETL, REST APIs, webhooks, event streaming) is a bonus. At the centre of the company’s culture is freedom and openness which takes a lot of More ❯