Top Machine Learning Jobs in London

The Pre-Sales AI Director partners with enterprise customers to develop AI transformation roadmaps and scope pilot engagements, focusing on high-value AI use cases and aligning customer needs with technical capabilities.

The Product Manager will lead the credit card product strategy, working on mobile app features, customer acquisition, and analytics to drive growth.

As an Associate AI/ML Researcher, you will apply advanced AI/ML methods to enhance trading strategies, improve models, and drive predictive analytics in trading systems.

The Staff Machine Learning Engineer, Simulation will build a research engineering team to advance AV simulations, collaborating with teams to use large models for sim realism, design experiments, and integrate models into applications.

Join a small AI startup solving email problems, requiring deep experience in software, AI/ML, product intuition, and startup culture.

Lead the AI product strategy at Goodnotes, overseeing development across various AI initiatives and ensuring alignment with company vision.

As a Machine Learning Engineer, you will develop software solutions using machine learning, collaborate with clients, and deliver impactful projects working within cross-functional teams.

The role involves designing and implementing machine learning solutions, managing projects from idea to deployment, and optimizing models using AWS and Docker.

The internship involves research and development in AI and NLP, focusing on semantic systems, embedding-based retrieval, and collaboration on publishable research.

The Director of AI will drive AI strategy across the company, manage R&D efforts, lead adoption of AI workflows, and establish success metrics.

Drive strategic revenue and transform enterprise client relationships through long-term engagements, navigating challenges and delivering measurable business value.

The Machine Learning Engineer will design and build ML pipelines, integrate models for simulations, and interact with customers to enhance engineering solutions.

Lead global risk and trading teams, implement quantitative risk models, analyze order flows, detect trading abuse, and enhance risk processes.

As a Senior Research Engineer, you will manage data lifecycle for researchers, build a human-centric data lake, and enhance model performance through high-quality datasets in an AI-driven environment.

Drive independent, high-impact research on frontier AI topics, publish findings, collaborate widely, and mentor new researchers in the field.

The Global Digital Marketing Senior Manager will elevate brand presence across digital channels, lead data-driven marketing strategies, and enhance consumer experience through automation and advanced analytics.

This role leads international legal matters, including contract negotiation, compliance management, and advising on competition and employment law, requiring ethical judgement and collaboration.

The Technical Product Manager leads product discovery, collaborates with stakeholders, and manages the product lifecycle focusing on AI-driven solutions and digital products.

As an AI/ML Engineer, you'll develop AI solutions, conduct data analyses, build production-grade systems, and integrate advanced recommendation engines.

As Lead Data Scientist, oversee project teams delivering AI solutions, mentor junior team members, and shape technical strategy for financial services clients.

The Head of Data & AI leads initiatives in data and AI, focusing on remediation, governance, infrastructure development, and collaboration with various teams to ensure ethical AI use and data-driven decision-making.

As a Data Scientist Analyst, you will assist in client projects, analyze data, support model development, and communicate insights effectively.

The role involves developing, fine-tuning, and optimizing large language models, building ML infrastructure, and implementing CI/CD practices for AI/ML systems.

Develop ML systems for autonomous driving, lead projects using RL and deep learning, and collaborate with cross-functional teams to improve Waymo's technology.

The role involves developing an ML research and deployment pipeline, implementing best practices in model and feature management, and ensuring robustness in production through effective solutions and collaboration.