Top Machine Learning Jobs in London

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.

As a Software Engineer on the Applied ML team, you will design and implement solutions for customers, utilizing AI and ML technologies throughout the product lifecycle.

The Machine Learning Engineer will optimize large scale training jobs on GPU clusters, implement efficiency improvements, and collaborate with research teams for enhanced model training performance.

Lead a team to design and develop scalable machine learning systems for drug discovery, mentoring engineers and ensuring software excellence.

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

As a Staff Software Engineer, you will build platform infrastructure for real-time data processing, solve optimization problems, and implement APIs and UI designs.

As a Machine Learning Software Engineer, you'll develop scalable models with ML techniques, collaborate with researchers and engineers, implement distributed training, and mentor junior colleagues.

Design and implement advanced machine learning models for autonomous vehicles, focusing on prediction and motion planning, while leading projects and collaborating with various teams.

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

Develop and integrate machine learning solutions for fraud prevention in transactions, analyze data using SQL and Python, and manage the complete lifecycle of ML solutions.

The Senior Machine Learning Engineer will design and implement algorithms for detecting anomalies in games, lead research, and mentor junior members.

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

Lead Machine Learning Engineer to oversee AI projects, guide technical direction, manage teams, and innovate in building scalable ML systems.

As a Lead Machine Learning Engineer, you will guide complex AI projects, oversee technical direction, mentor engineers, and drive innovation across teams.

Lead the development and deployment of scalable AI systems, mentor junior engineers, and collaborate with teams to solve client challenges.

As a Senior Machine Learning Engineer, you'll design, build, and scale machine learning systems, developing production-grade pipelines and collaborating with engineers and data scientists.

As a Staff Machine Learning Engineer, you'll design and deploy ML systems, lead projects, ensure MLOps best practices, mentor engineers, and collaborate across teams to drive enterprise innovation in AI.

As an AI/ML Scientist Intern, you'll develop and deploy AI solutions, assist in testing models, collaborate on projects, and stay informed on AI technologies.

As an ML Engineer, you will build and optimize AI models for rota scheduling, enhance data pipelines, and collaborate with engineering teams to integrate AI into workflows.

The Applied Scientist will solve impactful problems using deep learning models and statistical analysis, translating commercial goals into technical solutions.

As a Senior Machine Learning Engineer, you will develop models, optimize existing solutions, automate ML workflows, and contribute to engineering production-ready software using machine learning and cloud tools.

Lead the design and implementation of machine learning solutions while mentoring engineers, driving innovation, and ensuring high-quality standards in production software.

As a Machine Learning Engineer, you will develop and implement ML algorithms and GenAI solutions, productionize algorithms, and foster a collaborative data science culture while identifying impactful opportunities across products.

Drive measurable value through data science. Develop robust ML models, build scalable AI solutions, and collaborate for impactful results.