Top Machine Learning Jobs in London

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.

The role involves developing and deploying ML workflows, teaching best practices, and contributing to infrastructure scalability for AI initiatives.

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

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

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

Research and develop machine learning algorithms for automation, collaborating with product teams to implement scalable models in a dynamic environment.

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 role involves developing anomaly detection algorithms for game QA, mentoring junior members, collaborating on model deployment, and leading research efforts in machine learning.

As a Senior Machine Learning Engineer, you'll design and implement ML models, develop data pipelines, and collaborate on AI features at Mural.

N-iX seeks a Data Engineer with MLOps experience to create scalable ML pipelines, deploy models, and contribute to best practices in data engineering and coding.

The Tech Lead will architect and implement AI systems, oversee model integration and ensure compliance with security standards while collaborating with teams on scalable solutions.

The Operations Manager will lead and scale field service teams in Europe, ensuring safe and high-quality installations, managing logistics, and enforcing compliance with safety standards.

The AI Director will oversee ML bot development and implementation, identify AI opportunities, educate teams, and prototype AI solutions.

The AI & ML Engineer will oversee the entire AI/ML lifecycle, collaborating with stakeholders to develop and implement scalable, efficient solutions while ensuring the security and robustness of ML systems.

Lead the development and scaling of production ML systems at Foundation Health, mentoring a team and collaborating with engineers to enhance healthcare workflows.

The Machine Learning Engineer will develop AI-driven features, deploy scalable systems, and enhance reliability while collaborating with teams to integrate AI solutions.

The Machine Learning Recruiter will connect G-Research with top talent in AI and ML, manage recruitment, and represent the company culture.

The Data Analyst will manage customer accounts, conduct data investigations, develop machine learning models, prevent fraud, and work with various teams to enhance customer support.

Lead the development of Lightricks' AI infrastructure, manage backend engineers, and oversee system design and technical strategy for cutting-edge AI models in production.

The Senior Machine Learning Engineer will enhance ML model performance in NLP, deploy models, collaborate with teams, and lead design proposals.

As a Software Engineer, you'll lead AI implementation projects for the UK public sector, designing innovative solutions and engaging directly with customers to address complex challenges.

The AI/ML Engineer will develop AI-powered simulation systems, maintaining LLM orchestration and semantic search pipelines while collaborating with engineers on scientific accuracy.

Lead Machine Learning initiatives focusing on fraud prevention and customer personalization, fostering collaboration across teams to enhance banking experiences through advanced ML models.

As a Senior Staff ML Scientist at Monzo, you'll define ML strategy, mentor talent, and integrate ML into business operations, enhancing customer support and efficiency.

As a Machine Learning Engineer, you will manage ML infrastructure, optimize model performance, and support the deployment of machine learning models in a production environment.