Top Machine Learning Jobs in London

As a Senior Machine Learning Engineer, you will lead the development of AI systems, design production-grade ML software, and mentor junior engineers while engaging with clients on technical strategies.

The Senior ML Systems Engineer will build and maintain the training framework for large-scale language models, focusing on distributed training and performance optimization.

Design, build, and productionise end-to-end ML systems for a matching platform: feature pipelines, model development (ranking/scoring/similarity), SageMaker-based training and deployment, low-latency inference, monitoring and drift detection, explainability (SHAP), ML governance, and MLOps/CI-CD improvements.

Lead design and delivery of enterprise ML architecture and MLOps for a matching platform: define data/feature pipelines, SageMaker-based training and inference, governance, explainability, telemetry, drift detection, low-latency serving, and mentor engineering teams to ensure scalable, secure, auditable ML systems.

As the Head of Machine Learning Engineering, you will define the ML strategy, lead teams, deliver scalable solutions, and shape AI governance for enhanced customer travel experiences.

Join a team to develop and evaluate large-scale machine learning models for drug discovery, collaborating with scientists and engineers.

The Machine Learning Engineer will design, deploy, and optimize AI-powered solutions, collaborating with data scientists and engineering teams to bridge the gap between experiments and production, ensuring reliability and scalability.

The role involves optimizing ML model performance, focusing on efficient training, low-latency inference, and understanding low-level GPU and networking technologies.

Join a Machine Learning team to build deep learning models for trading strategies, collaborating with researchers and traders in a dynamic environment.

Technical lead for data and NLP: improve search precision/recall and performance, optimize search algorithms, design and implement agentic LLM workflows, build and maintain data pipelines, and lead ML model development and deployment.

The Applied AI Engineer will onboard clients on Mistral AI products, manage complex integrations, and drive technological transformations through collaboration with stakeholders.

The ML Ops/Data Engineer will ensure reliability and scalability of ML systems, manage data pipelines, monitor performance, and collaborate with teams for optimization.

The Senior Machine Learning Engineer will lead the development and deployment of AI systems, designing scalable ML software, collaborating with teams, and mentoring juniors.

The Machine Learning Engineer will build, refine, and optimize AI/ML prototypes while collaborating with teams on technical documentation, deployment, and model integration.

The Senior AI/ML Engineer will design and optimize scalable systems, productionize AI prototypes, solve performance issues, and collaborate with teams on innovative solutions.

Design, build, deploy, and maintain scalable AI/ML pipelines and production models (including LLMs). Collaborate with data scientists and engineers to optimize model performance, latency, and cost on cloud platforms using MLOps practices, containerization, and CI/CD. Integrate AI capabilities into client and internal applications and monitor models in production.

Lead development of machine learning models, enhance user feedback analysis, drive technical direction, and optimize evaluation systems for autonomous vehicles.

As a Research Engineer in ML, you'll optimize large-scale ML systems, collaborate with Research Scientists, enhance models, and implement algorithms in Python.

As a Senior Software Engineer, you'll design and build AI applications in Python, optimize performance, collaborate with clients, and lead technical practices. You will ensure high-quality standards and participate in agile development processes.

Design, develop, and deploy scalable machine learning solutions while collaborating with cross-functional teams and optimizing model performance.

Lead the Voice team at Rasa, focusing on mentoring engineers, driving processes, and delivering voice features while maintaining strong communication and async practices.

The Senior Machine Learning Ops Engineer will design and build machine learning operations infrastructure, manage ML pipelines, experiment tracking, model deployment, and collaborate with engineering teams to enhance data and ML processes.

As a Senior Machine Learning Engineer, you will enhance product features, optimize computer vision algorithms, mentor team members, and stay updated with research.

As a Research Engineer in Reinforcement Learning, you will develop and optimize RL infrastructure, push boundaries in AI research, and collaborate on scalable systems for large language models.

The Senior Machine Learning Engineer will design and productionize ML models for customer support and compensation at Deliveroo, enhancing customer experience and trust. Responsibilities include model ownership, evaluation framework development, and collaboration across teams.