51 to 75 of 87 MLOps Jobs in Central London

Data/MLOps Engineer Hybrid Working - 2 days p/w in office (Liverpool Street, London) Pays £75k-£85k Data/MLOps Engineer - Python, SQL, AWS, Azure Oliver Bernard have partnered with a retail bank undergoing a data transformation. You'll be joining their core Data team and be responsible for deploying tooling through cloud platforms, utilising new LLM models … and building out new pipelines. Data/MLOps Engineer - Python, SQL, AWS, Azure Key Skills and Experience: Python SQL Tableau, PowerBI Terraform AWS, Azure This role is hybrid working from their offices in Liverpool Street, EC2M 7PY (2 days p/w). VISA sponsorship is not available for this role. Budget is £75k-£85k + benefits including bonus. … stage interview process - 1st stage call with manager, final stage with team. Data/MLOps Engineer - Python, SQL, AWS, Azure More ❯

. API Development: Experience building data-centric APIs, especially with FastAPI on serverless platforms like Google App Engine . Streaming Data: Practical experience building real-time data pipelines. DevOps & MLOps: Knowledge of Infrastructure as Code (Terraform), MLOps principles, and containerization (Docker, Kubernetes). What They Offer Work that impacts elite football performance and club-wide success Access to real-world More ❯

. API Development: Experience building data-centric APIs, especially with FastAPI on serverless platforms like Google App Engine . Streaming Data: Practical experience building real-time data pipelines. DevOps & MLOps: Knowledge of Infrastructure as Code (Terraform), MLOps principles, and containerization (Docker, Kubernetes). What They Offer Work that impacts elite football performance and club-wide success Access to real-world More ❯

This role is central to making that happen. 🎯 What you'll do: Lead a team of engineers to design and deploy AI/ML and generative AI models Architect MLOps and LLMOps pipelines and coach our data science team on scalable, high-quality code Monitor model performance, define KPIs, and continuously improve solutions Collaborate with cross-functional squads to deliver … it’s in CPG, retail, or health) Line management experience Passion for engineering & strong track record of delivering data-driven solutions that stick Hands-on experience with AzureML, Databricks, MLOps frameworks & CI/CD A strategic, problem-solving mindset and effective communication skills A passion for collaboration, coaching, and continuous learning 🎁 What you’ll get: Hybrid working + competitive salary More ❯

Collaborate with engineers and researchers to develop new AI features Evaluate model performance and drive continuous improvements Translate business needs into high-impact AI solutions Implement strong testing and MLOps practices What will you bring? 5+ years in software engineering or ML development Deep Python expertise and experience building production systems Strong knowledge of ML techniques, tooling (e.g. MLflow, W More ❯

like LoRA, QLoRA, SFT, PEFT, and RLHF Inference & Acceleration: Serve models using vLLM, DeepSpeed, Triton, TensorRT Multi-Agent Orchestration: Work with LangChain, AutoGen, CrewAI, DSPy and similar tools Cloud & MLOps (AWS): Deploy with SageMaker, Bedrock, Lambda, S3, ECS, EKS Full-Stack Integration: Build APIs (FastAPI, Flask) and integrate with React, TypeScript, Node.js Vector Search: Use FAISS, Weaviate, Pinecone, ChromaDB, OpenSearch More ❯

fast-paced startup environments UK-based and available to work 2–3 days per week in-office (London) Bonus Points Experience in healthcare, medtech, or clinical systems Familiarity with MLOps tooling (MLflow, Kubeflow, Vertex Pipelines More ❯

innovate and the support of a collaborative and expanding team, you'll have the chance to create something impactful from the ground up. Main Responsibilities Collaborate with engineering and MLOps teams to develop scalable, robust, and production-ready solutions Design and deliver data science and GenAI solutions that drive tangible value for clients Act as a trusted advisor, translating complex More ❯

inference using vLLM, DeepSpeed, TensorRT, Triton, and other acceleration frameworks. Multi-Agent Systems : Develop and integrate agentic capabilities using frameworks such as LangChain, CrewAI, AutoGen, and DSPy. AWS Cloud & MLOps: Deploy scalable machine learning workloads on AWS using services like SageMaker, Bedrock, Lambda, S3, DynamoDB, ECS, and EKS. End-to-End AI Product Development : Work across the full ML lifecycle More ❯

cloud-native AI solutions. Hands-on experience with Azure Cognitive Services, OpenAI APIs, and vector search (e.g., Azure AI Search, FAISS, CosmosDB, Pinecone, etc.). Experience in AI security, MLOps, and deploying scalable AI solutions. Ability to troubleshoot and optimize AI models for performance and accuracy About Capgemini Capgemini is a global business and technology transformation partner, helping organizations to More ❯

findings to non-technical stakeholders. Highly desirable skills include: Football Analytics Domain: Significant plus if experienced with football datasets (event, tracking, etc.) and visualization libraries like mplsoccer . Advanced MLOps & Modelling: Deeper experience with the Vertex AI lifecycle (especially Pipelines ) and advanced modelling techniques relevant to football (player valuation, tactical analysis). Bayesian Modelling: Experience with probabilistic programming (e.g., PyMC More ❯

documents, index embeddings (Pinecone, FAISS, Weaviate), and build similarity search features. Rapid Prototyping: Create interactive AI demos and proofs-of-concept with Streamlit, Gradio, or Next.js for stakeholder feedback; MLOps & Deployment: Implement CI/CD pipelines (e.g., GitLab Actions, Apache Airflow), experiment tracking (MLflow), and model monitoring for reliable production workflows; Cross-Functional Collaboration: Participate in code reviews, architectural discussions More ❯

with the full RAG pipeline, including vector embeddings , rerankers , and data indexing in databases like MongoDB. Practical knowledge of LLM fine-tuning, prompt engineering, and performance optimization. Familiarity with MLOps principles and tools, including CI/CD with GitHub Actions . A strong interest in computer vision and an understanding of object detection models like Ultralytics YOLO11 is a significant More ❯

model deployment, and monitoring . Proficient in a major backend language and related ML/AI libraries (e.g. Tensorflow & PyTorch , etc), with a preference for Go. Experience with an MLOps platform like Kubeflow. Demonstrated ability to transition models from prototyp e to production . Experience assessing various AI/ML technologies and models for fit to problem space , including scenarios More ❯

Head of Data Science London – Hybrid Up to £115,000 + Benefits The Opportunity A leading organisation within the Insurance space is seeking a Head of Data Science to lead a team of data scientists and drive high-impact machine More ❯

familiarity with common ML frameworks (Scikit-learn, XGBoost/LightGBM, TensorFlow, PyTorch) Exposure to LLMs or NLP techniques is a plus Experience with cloud-based data platforms and modern MLOps practices Details London (hybrid) £70,000 – £90,000 base Opportunity to work on both greenfield and large-scale ML projects in a mission-led environment Apply now to learn more More ❯

world impact using the latest Large Language Models (GPT, Gemini, LLaMA). What you’ll do: Develop and fine-tune state-of-the-art generative AI models Build scalable MLOps pipelines for production-ready AI solutions Collaborate with cross-functional teams to deliver business value Work hands-on with TensorFlow, PyTorch, Hugging Face, and GCP’s Vertex AI What you More ❯

Design and implement pipelines that support retrieval-augmented generation, internal AI tools, and scalable content delivery. Experience with vector databases, agent frameworks, or data workflows is highly relevant. 🔹 Deployment & MLOps: Own model deployment pipelines, including API-based serving, monitoring, and cloud infrastructure (AWS preferred, but others welcome). Bonus points for edge/offline deployment experience. 🔹 Product & Strategy: Work directly More ❯

identifying cyber threats (URLs, domains, phishing, botnets, etc.) Proficient in a major backend language (ideally Golang) and related ML/AI libraries (e.g. Tensorflow & PyTorch, etc.) Experience with an MLOps platform like Kubeflow. Demonstrated ability to transition models from prototype to production. Experience assessing various AI/ML technologies and models for fit to problem space, including scenarios where RAG More ❯

e.g., WebGL). Deep knowledge of modern UI frameworks (e.g., React, Tailwind). Familiarity with molecular or protein visualisation tools (e.g., Mol*). An interest in model serving or MLOps workflows. Responsibilities Develop and maintain both front-end and back-end components of our platform. Design intuitive, visually compelling web interfaces for molecular data. Optimize performance throughout the stack—from More ❯

Python and SQL (BI tools such as SuperSet, Tableau or PowerBI is a bonus) Hands-on experience in machine learning model development, evaluation, and production deployment, with familiarity in MLOps principles to build scalable and standardised workflows and implement effective ML monitoring systems Proven ability to create polished presentations and effectively communicate insights to customers with attention to detail Have More ❯

model optimization (i.e. quantization, pruning) and model deployment frameworks such as TensorRT, ONNX Runtime, and OpenVINO. Proficiency with CUDA programming and optimizing code for GPU acceleration. Strong background in MLOps practices, including CI/CD using GitHub Actions and containerization with Docker. Excellent problem-solving skills and the ability to thrive in a fast-paced, high-intensity environment. Experience contributing More ❯

and deploying object detection models, particularly within the YOLO family. Familiarity with model optimization techniques such as quantization and pruning, and deployment frameworks like TensorRT and OpenVINO. Experience with MLOps tools and practices, including version control (Git), Docker, and CI/CD with GitHub Actions. Excellent problem-solving skills and the ability to perform in a fast-paced, high-intensity More ❯

CD platforms for building reliable deployment pipelines (e.g. GitLab CI, ArgoCD) Worked with Kubernetes and infrastructure as code tools such as Terraform for scalable system deployment Are familiar with MLOps practices and tools, and monitoring machine learning systems in production This role will report to the VP of Engineering and can be based anywhere within a 3-hour time zone More ❯

Python/Go AI Engineer - Python, Go, AI/ML, Terraform & AWS Key skills & experience: High level knowledge of of Python/Go Hands on experience building AI Pipelines MLOps experience Cloud engineering skills with Docker, Kubernetes, Terraform & AWS This role is hybrid with 2-3 days a week required in a London based office Base salary of up to More ❯