76 to 85 of 85 MLOps Jobs in Central London

AI features, including retrieval-augmented generation (RAG), internal LLM-based tools, and content delivery workflows. Experience with vector stores, agent frameworks, or scalable data workflows is all relevant here. MLOps & Deployment: Build and maintain the infrastructure behind our AI stack – including serving models via APIs, monitoring performance, and deploying systems to the cloud. AWS is a plus, but experience with More ❯

AI features, including retrieval-augmented generation (RAG), internal LLM-based tools, and content delivery workflows. Experience with vector stores, agent frameworks, or scalable data workflows is all relevant here. MLOps & Deployment: Build and maintain the infrastructure behind our AI stack – including serving models via APIs, monitoring performance, and deploying systems to the cloud. AWS is a plus, but experience with More ❯

AI features, including retrieval-augmented generation (RAG), internal LLM-based tools, and content delivery workflows. Experience with vector stores, agent frameworks, or scalable data workflows is all relevant here. MLOps & Deployment: Build and maintain the infrastructure behind our AI stack – including serving models via APIs, monitoring performance, and deploying systems to the cloud. AWS is a plus, but experience with More ❯

to join early, build real AI systems, and take ownership of core architecture and product direction. What You’ll Do Build and own core AI/ML systems (Python, MLops/LLMops pipelines, integrations, data retrieval) Architect and scale a product that works across messy enterprise data (SharePoint, Slack, Outlook, etc.) Define infrastructure and engineering best practices from the ground … up What We’re Looking For 3–6+ years AI software engineering and deployment experience Strong exposure to MLops/LLMops, ideally in real-world AI product builds Experience with unstructured data, search/re-ranking, or retrieval systems (e.g., RAG) A “builder” mindset, fast, hands-on, pragmatic, collaborative Excited by early-stage start-up life More ❯

machine learning models in production Strong skills in Python , SQL , and modern cloud environments (AWS preferred) Experience with services like SageMaker , Lambda , or real-time processing tools Understanding of MLOps , versioning, and model monitoring best practices Practical mindset with the ability to balance technical depth with speed of delivery Bonus: exposure to large-scale digital data environments, classification problems, or More ❯

but Valuable) Worked at a Pre-Seed or Seed-stage startup through to Series A Built or deployed software used by enterprise customers Experience with applied machine learning or MLOps (not just academic or notebook-based work) Exposure to event-driven architectures, streaming systems (Kafka, etc.), or real-time data pipelines Frontend experience in React, TypeScript, or similar modern frameworks More ❯

leading enterprises deploy cutting-edge AI agents. The ideal candidate will bring a blend of: experience with traditional data science and machine learning (solid stats, programming, ideally exposure to MLOps, etc.) critical: up-to-speed with the latest AI tools and active (daily) leverage of the same (co-pilots, MCPs, agentic workflows, RAGs, LLMs) - we appreciate these are new and More ❯

security What you need: Extensive experience in AI architecture on GCP with proven client impact Strong network and relationships within Google teams Deep understanding of AI/ML frameworks, MLOps, and cloud security Excellent stakeholder management and communication skills Why join? Influence strategic AI initiatives at scale Access to advanced tools and elite AI talent Competitive salary, flexible working, and More ❯

Machine Learning Engineer 18 month project, 6 month rolling contracts. Rate negotiable but upwards of 600 p/d. Looking for people with the following skillset: Python, Pytorch, Tensorflow, Langgraph, Langchain, CrewAI, LlamaIndex etc ML Ops VertexAI Prompt Engineering 1st More ❯

Our Client Founded 5 years ago and already 100 people strong with offices in both London and NY, our client has built a robust and explosive MLops business. Series B funded (raised over $30m), they are currently the youngest AI business to raise a Series B from the YCombinator portfolio! They have built a product that leans into blending machine More ❯