101 to 120 of 120 MLOps Jobs in Central London

Using frameworks like LangChain , PyTorch , and TensorFlow to bring models into production. Working with AWS Bedrock, SageMaker , or GCP Vertex AI to deliver scalable cloud-based systems. Implementing strong MLOps and LLMOps practices - from CI/CD and model monitoring to cost and performance optimisation. Partnering with Data Engineers to ensure the pipelines and data structures feeding the models are …/ML or LLM-driven products. Experience with cloud ML platforms (AWS SageMaker, Bedrock, Vertex AI, etc.). Familiarity with LangChain or similar orchestration frameworks. A solid understanding of MLOps and how to take models from concept to production. A collaborative mindset - you enjoy working closely with Product and Data teams and mentoring others when needed. Curiosity, experimentation, and a More ❯

Using frameworks like LangChain , PyTorch , and TensorFlow to bring models into production. Working with AWS Bedrock, SageMaker , or GCP Vertex AI to deliver scalable cloud-based systems. Implementing strong MLOps and LLMOps practices - from CI/CD and model monitoring to cost and performance optimisation. Partnering with Data Engineers to ensure the pipelines and data structures feeding the models are …/ML or LLM-driven products. Experience with cloud ML platforms (AWS SageMaker, Bedrock, Vertex AI, etc.). Familiarity with LangChain or similar orchestration frameworks. A solid understanding of MLOps and how to take models from concept to production. A collaborative mindset - you enjoy working closely with Product and Data teams and mentoring others when needed. Curiosity, experimentation, and a More ❯

Using frameworks like LangChain , PyTorch , and TensorFlow to bring models into production. Working with AWS Bedrock, SageMaker , or GCP Vertex AI to deliver scalable cloud-based systems. Implementing strong MLOps and LLMOps practices - from CI/CD and model monitoring to cost and performance optimisation. Partnering with Data Engineers to ensure the pipelines and data structures feeding the models are …/ML or LLM-driven products. Experience with cloud ML platforms (AWS SageMaker, Bedrock, Vertex AI, etc.). Familiarity with LangChain or similar orchestration frameworks. A solid understanding of MLOps and how to take models from concept to production. A collaborative mindset - you enjoy working closely with Product and Data teams and mentoring others when needed. Curiosity, experimentation, and a More ❯

building data-centric APIs using FastAPI , especially in serverless environments (e.g., Google App Engine) Streaming Data: Familiarity with real-time data pipelines and data ingestion at scale DevOps/MLOps: Exposure to Terraform , Docker , Kubernetes , and MLOps workflows What They Offer A chance to work on real-world data that impacts elite football performance Access to high-value datasets , sports More ❯

A global lifestyle brand is hiring a Data Science Manager to lead personalisation efforts within its CRM ecosystem. The role sits in the Consumer Intelligence and Experience (CIX) team, which drives customer engagement through predictive analytics and insights across all More ❯

Role As our first senior AI hire, you’ll take ownership of designing and building the foundation of our AI ecosystem. You’ll shape the infrastructure strategy, establish our MLOps pipelines, and work closely with product and data teams to enable seamless model development and deployment. Once the environment is established, you’ll play a key role in recruiting and … mentoring two mid-level AI engineers who will join your team. Responsibilities Architect, build, and maintain an in-house AI environment (on-prem or hybrid cloud). Design MLOps workflows for training, deploying, and monitoring models. Integrate and manage containerized AI engines (Docker/Kubernetes). Establish best practices for model versioning, data pipelines, and reproducibility. Collaborate with ML and … or on-premise platforms (non-cloud environments). Solid understanding of data pipelines, APIs, and scalable system architecture. Preferred Experience leading small teams or mentoring other engineers. Familiarity with MLOps tools and best practices. Background in integrating AI solutions into enterprise products. Awareness of privacy, bias mitigation, and model explainability techniques. What We Offer Opportunity to design and own the More ❯

. Develop pipeline programming using Python, Spark, and SQL; integrate APIs for seamless workflows. Support Machine Learning and AI initiatives, including NLP, Computer Vision, Time Series, and LLMs. Implement MLOps, CI/CD pipelines, data testing, and quality frameworks. Act as an AI super-user, applying prompt engineering and creating AI artifacts. Work independently while providing clear justification for technical … Proficient with cloud platforms (Snowflake, AWS fundamentals). Solid understanding of data architecture, warehousing, and modeling. Programming expertise: Python, Spark, SQL, API integration. Knowledge of ML/AI frameworks, MLOps, and advanced analytics concepts. Experience with CI/CD, data testing frameworks, and versioning strategies. Ability to work effectively in multi-team, vendor-integrated environments. Why This Role Join a More ❯

🔍 ML Ops Engineer – Cloud, Data, and AI Are you passionate about shaping the future of data and cloud technology? We’re partnering with a forward-thinking financial organization investing heavily in its data and AI capabilities — and they’re looking More ❯

MLOps Engineer Contract London based (hybrid or onsite depending on preference) Outside IR35 £600 to £650 per day I am supporting a client in London who is preparing to scale their machine learning capability. They need an experienced MLOps Engineer who can take models from development into a reliable production environment and keep everything running smoothly throughout the lifecycle. What … stability and performance across the ML platform. Key skills • Strong Python for production environments. • Solid experience with Azure for ML workloads including compute, networking and storage. • Good knowledge of MLOps tools such as MLflow, Azure ML, Kubeflow or similar. • Strong background in CI and CD using GitHub Actions, Azure DevOps or similar. • Experience working in containerised environments using Docker and … have • Experience working on large scale data or ML projects. • Good understanding of data engineering fundamentals. • Experience working in regulated or high availability environments. If you're an experienced MLOps Engineer feel free to apply or send your C.V to nokakpu@revoco-talent.co.uk MLOps Engineer More ❯

powered solutions . Lead on data strategy , from collection and simulation to training and validation. Ensure AI safety, ethics, explainability , and compliance with defence standards. Define best practices in MLOps , model evaluation, and continuous integration. Essential Skills & Experience MSc (or PhD) in Computer Science, Artificial Intelligence, Machine Learning, Robotics, or related engineering field . 5+ years of experience in AI … or sensor fusion . Excellent communication and problem-solving skills. Desirable Extras Publications in leading AI/ML or robotics conferences (e.g. NeurIPS, CVPR, ICLR, ICRA). Experience with MLOps pipelines, synthetic data, and model optimisation for edge devices . Understanding of sensor fusion, perception pipelines , and AI safety principles . What’s on Offer Highly competitive base salary. Generous More ❯

Job Title: MLOps Engineer Location: On-site, 5 days per week Total Compensation: Up to £200,000 We are seeking an experienced MLOps Engineer to join a forward-thinking trading organisation. This is an exciting opportunity to design and implement the infrastructure that powers advanced machine learning workflows in a production trading environment. Key Responsibilities: Feature Store & Data Lake: Build … scalable infrastructure for time-series feature storage, retrieval, and versioning optimised for ML workloads. MLOps Pipelines: Design end-to-end workflows for data ingestion, feature engineering, model training, backtesting, and deployment. Data Ingestion Layer: Connect raw data streams into structured, queryable formats (Parquet/Delta Lake). Production Serving: Deploy feature computation and model inference with appropriate latency characteristics. Integration … execution systems to ensure seamless operations. CI/CD Pipeline: Implement and maintain robust continuous integration and deployment pipelines for ML models. Requirements: Strong experience in building and maintaining MLOps pipelines. Hands-on experience with feature stores, data lakes, and time-series data. Proficiency with modern data formats like Parquet and Delta Lake. Familiarity with production ML model deployment and More ❯

🚀 Data Engineer | AI Startup | Real-Time Data & ML Pipelines I’m currently partnered with a next-generation AI startup that’s building real-time intelligence systems capable of understanding and adapting to the world as it happens. They’re at More ❯

to benchmarking and ongoing improvements. Collaborate Across Teams — Work with Product, Infrastructure, and Customer teams to integrate models into workflows. Provide technical leadership aligned with business goals. Champion Data & MLOps — Maintain high data quality standards and develop scalable automation systems for seamless deployment and experimentation. Lead a team of ML Engineers Requirements PhD (or equivalent) in Computer Vision, Machine Learning … models in production. Strong Python skills with PyTorch or TensorFlow expertise. Deep understanding of modern CV architectures, especially LVMs and Transformers. Experience with multimodal data (images, video, text) and MLOps workflows. Hands-on, self-directed, evidence-driven, and collaborative, with excellent communication skills for both technical and non-technical audiences This is an excellent opportunity for an experienced Staff Computer More ❯

translate complex technical knowledge into clear evaluation criteria and insights. Key Responsibilities • Capability Framework Design: Develop and refine the assessment framework for AI and data technical roles — including architecture, MLOps, and applied AI functions. • Question and Exercise Creation: Design technical and scenario-based questions to assess AI understanding, solution design ability, and architectural thinking. • Talent Assessment: Evaluate existing AI talent … evaluations preferred. • Excellent communication and stakeholder engagement skills, with the ability to translate technical complexity into actionable insights. • Knowledge of cloud-based AI platforms (Azure, AWS, GCP) and enterprise MLOps environments a plus. • Prior consulting or advisory experience within large organizations is advantageous. More ❯

HGX B200 GPU nodes (96 NVIDIA B200 GPUs) and associated infrastructure • Managing Weka NeuralMesh distributed AI storage for high-speed data access and resilience • Implementing CI/CD and MLOps pipelines using Argo Workflows, Jenkins and GitHub • Monitoring platform performance using Zabbix, Prometheus and Grafana • Integrating SAN and Infiniband networking to achieve high throughput and reliability • Creating detailed documentation and … knowledge of NVIDIA GPU technologies, particularly GPU Operator and Run:AI • Familiarity with distributed storage and AI data systems such as Weka NeuralMesh • Experience with CI/CD and MLOps pipelines using Argo, Jenkins or GitHub • Knowledge of HPC networking including SAN and Infiniband integration • Strong troubleshooting and documentation skills with a collaborative mindset Desirable Experience • Certifications in Kubernetes, NVIDIA More ❯

Join us at Entrust At Entrust, we’re shaping the future of identity centric security solutions. From our comprehensive portfolio of solutions to our flexible, global workplace, we empower careers, foster collaboration, and build solutions that help keep the world More ❯

About the Team : You'll be joining the team leading Entrust's Identity portfolio, formerly known as Onfido (an AI- powered digital identity solution). Our technology helps businesses verify real identities using machine learning, ensuring secure remote customer onboarding. More ❯

Senior System Engineer (AI/ML) | Permanent position Location: Central London Onsite: 5 days a week (South Kensington/Waterloo) Salary: Up to £82,500 + Excellent Benefits Available position: 2 positions Our client, an IT consulting and services provider 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 Apply More ❯

Senior Product Manager – HealthTech Hybrid – 2 days Oxford, 1 day London, 2 from home! A world-class AI research organisation is quietly building a tech team that will tackle some of humanity’s biggest challenges - and they need a healthcare More ❯