Top Machine Learning Jobs in London

Leads global AI quality, accreditation, and conformity assessment activities, including obtaining EU AI Notified Body designation, developing regulatory processes, and ensuring consistent certification practices. The role advises internal teams and customers, represents BSI in international technical forums, establishes competency criteria, supports regulatory programs, identifies process improvements, and shapes the AI and machine learning business strategy. It requires expertise in global AI regulations, quality management, legislation, technical product areas, stakeholder influence, and people leadership.

Six-month PhD internship on the Central Execution Desk performing execution research: analyzing market microstructure, building simulation and analytics tools, designing and evaluating models, and working with large noisy datasets to support trading and execution decisions.

Lead and operationalize a company-wide AI governance program: build frameworks, assess AI risks and use cases, embed controls in SDLC, run governance council, liaise with Siemens consortium, handle regulatory compliance (EU AI Act, NIST AI RMF), produce reporting, and deliver training and documentation across Product, Engineering, Legal, Privacy, HR and Security.

Adjudicate automated vessel detections humans cant resolve: identify dark/spoofed/low-confidence contacts, investigate AIS/GNSS manipulation and ownership, produce sourced identification records, and supply labeled ground truth to improve detection models.

Lead product strategy and roadmap for Dentally, build and mentor a high-performing product team, embed discovery and data-informed practices, champion generative AI/automation, collaborate cross-functionally, adapt products for regional markets, drive adoption and revenue opportunities, and own recruitment and development of product staff.

Build scalable backend platform capabilities, infrastructure, tooling, and ML frameworks for Walmart’s Membership Experience Engineering team. Lead the full software development lifecycle, apply cloud-native architecture, design APIs and resilient systems, integrate AI and machine learning components, conduct design reviews, and ensure deployment, observability, and maintenance. Mentor engineers, influence technical decisions, collaborate with stakeholders, and use data-driven practices to improve engineering productivity and product outcomes.

Lead global strategy to optimize and modernize financial crime detection across transaction monitoring, customer risk rating, and fraud models. Drive transition from rules-based controls to AI/ML-driven detection, oversee model lifecycle governance, reduce false positives, ensure regulatory defensibility, and partner with Compliance, Technology, Data, Operations, and vendors to deliver measurable risk and operational improvements.

The role involves designing and developing tools in Python for trading and risk management, maintaining data pipelines, and collaborating with teams to enhance trading strategies using advanced techniques.

Join Waymo's Simulator team to research and productionize large foundation models that increase autonomous vehicle simulation realism. Design experiments, develop realism metrics, train/evaluate models, integrate models into simulators, and collaborate across Waymo engineering teams.

As a Principal Scientist in Biologics, you will shape Boltz Lab's platform by applying biological insights to machine learning models, guide model development, and influence product decisions for real-world biologics engineering.

As an Applied ML Engineer/Scientist, you'll adapt machine learning models to drug discovery problems, collaborating with domain experts and managing end-to-end modeling projects.

Build and maintain scalable web and mobile applications and APIs across a modern web stack. Collaborate with product and UX to implement features, ensure quality via testing and CI/CD, assess architecture, prototype new ideas, and support cloud infrastructure and observability.

The MLOps Engineer will optimize, deploy, and operate large-scale machine learning models for Boltz Lab, ensuring efficient and reliable performance across distributed systems while collaborating with ML Researchers.

Lead the development and integration of advanced safety systems for scientific AI applications, building a team and establishing a research strategy.

12-month graduate programme to build a prediction-markets trading operation for US sports: process live data, build probability models, develop high-frequency trading systems, analyse strategy performance, and implement risk/capital management tools. Strong cross-discipline collaboration and potential for permanent hire.

The role involves guiding the Data Science team to develop search and recommendation systems, working with commercial teams to deliver user-focused products, and managing multiple projects related to data science implementation.

Lead delivery of advanced analytics and AI solutions for global clients, design scalable analytics products, industrialise prototypes to production, embed measurement and experimentation, drive adoption across markets, and build analytics capability and thought leadership within the organisation.

Lead qualitative research for global FMCG clients, directing multi-market and innovation projects. Provide strategic leadership, design proposals, manage clients and delivery, apply AI-enabled methods, and translate findings into actionable insights while traveling for immersive fieldwork.

Lead the roadmap and delivery of Ohme's data and AI products: prioritize features, define requirements and success metrics, work hands-on with ML/data engineers to ship and iterate, liaise with commercial and ops teams, and drive adoption and measurable business outcomes.

Lead technical direction and delivery of large-scale AI/ML platforms. Architect microservices and shared libraries, align ML, data science and DevOps, coach distributed engineers, define production readiness, and drive hiring and standards across software engineering.

The Director of Design Technology leads the technical design practice, shaping tools, systems, and AI capabilities that empower the UX team for scalable product experiences.

As a Lead Applied Scientist, you will define research strategy, mentor teams, and innovate AI/ML solutions for legal and other professional sectors.

The Senior Research Engineer will develop and deliver scalable ML solutions, collaborate with teams, and apply innovative technologies in AI to impact professionals in legal and accounting fields.

Develop, research, and deploy systematic eFX trading strategies across intraday to longer horizons using public and proprietary data. Prototype models quickly, move successful research into production, monitor and analyze live models for improvement, and contribute materially to P&L targets while collaborating with a team and leveraging ML/AI techniques where appropriate.

Design, implement, and optimize a low-latency high-frequency trading platform for cryptocurrency markets; collect market data, disseminate orders, analyze throughput/latency, build performance tools, and develop access to historical data and simulation systems.