Top Machine Learning Jobs in London

As a Lead Learning Engineer, you'll develop AI-powered educational solutions using learning science, collaborate with teams, and ensure products improve learning outcomes.

The Senior Machine Learning Engineer will develop ML models for biological data, improve scalability and interpretability, and collaborate with various teams for biomedical applications.

As a Data Analyst III, you will analyze data, create visualizations, and provide insights using AI tools to support business decisions while collaborating with stakeholders.

The role involves building infrastructure for training open source foundation models, with emphasis on autonomy and contributing in a dynamic team.

The Research Engineer will develop and optimize AI-driven video compression models, design training pipelines, and collaborate on research outputs and innovations.

Seeking a Senior Product Engineer to build secure systems for healthcare, integrate AI, and enhance patient care navigation. Responsibilities include delivering high-quality code, managing technical debt, and collaborating with product teams.

The role involves managing the pre-sales process by conducting technical validations, collaborating with sales and customer success teams, and creating necessary documentation while ensuring customer satisfaction and smooth handover.

Lead a squad of engineers to build core products, drive delivery of features, mentor team members, and foster innovation and collaboration.

The Senior Machine Learning Engineer will work on innovative R&D projects, collaborate across teams, and mentor others while focusing on advanced speech technology.

Lead technical engagements at a large Oil & Gas customer, developing strategies, coaching teams, and delivering tailored data solutions using Databricks.

As a Senior Specialist Solutions Architect, you will guide customers in developing production-grade ML applications, provide technical support, and mentor others while leveraging data science and ML skills.

Research Scientists develop algorithms for embodied AI, design and implement solutions for robotic agents, and work on large-scale training. They collaborate with teams to tackle real-world problems and present findings.

The SVP, Data, Technology & Analytics will lead WPP's data vision for the UK Government, overseeing multiple teams to ensure strategic integration and operational excellence, while fostering client partnerships and innovation.

In this role, you'll manage exposure data for non-natural catastrophe risks, develop predictive models, collaborate with underwriters, and generate analytics reports to enhance risk assessment processes.

The Senior Product Manager will lead initiatives in Network Efficiency, optimize logistics, and deliver impactful solutions by collaborating with various teams.

Lead the product strategy for Jumio's ID Verification solutions, overseeing product lifecycle, team performance, and collaboration with engineering and marketing, ensuring compliance and customer needs are met.

The Senior FinCrime Product Owner will design and implement a financial crime prevention product, develop strategy, and lead product delivery at Deblock.

As the Lead Data Scientist, you will provide technical leadership, oversee project delivery, mentor teams, engage with clients, and contribute to strategic initiatives in retail and consumer AI solutions.

Lead the technical direction and delivery of innovative AI projects, design ML systems, engage with customers, and mentor team members.

The role involves managing strategic enterprise relationships, executing multi-threaded sales cycles, showcasing AI capabilities, and fostering growth across large organizations.

The role involves building and implementing machine learning models, collaborating with cross-functional teams to solve complex problems in data science.

Responsible for the roadmap of a technical product, collaborating with engineers and stakeholders to develop, launch, and grow products.

The Lead ML Engineer is responsible for deploying ML models, ensuring production readiness, monitoring model performance, and providing technical leadership within the analytics and AI team.

Lead the Machine Learning team, ensuring quality delivery of ML models. Collaborate with stakeholders and foster an experimental culture in AI/ML.

Design, build, and deploy end-to-end ML and generative AI solutions (ranking, recommender, chatbots, agentic systems). Handle data engineering, feature engineering, modeling, evaluation, deployment, monitoring, and cross-functional communication to deliver business impact.