Top Machine Learning Jobs in London

Design, build, test, and maintain scalable regulatory reporting applications and data pipelines. Translate regulatory requirements into technical solutions, investigate reporting exceptions, reconcile data, optimize processing frameworks, and support the full software development lifecycle with monitoring and automation.

As a Senior Lead AI Solutions Consultant at Braze, you will increase revenue by promoting the AI portfolio, leading demos, and educating stakeholders about AI solutions while fostering collaborative relationships with clients.

11-week internship performing quantitative research to develop, backtest, and implement automated trading strategies. Translate mathematical models into code, analyze unconventional data sources, conduct statistical research (ML, time-series, NLP), and collaborate with senior researchers to refine trading signals and monetize models.

The intern will work on developing high-performance research platforms, create tools for trading strategies, and collaborate with teams to innovate financial technology.

Conduct original research applying machine learning, deep learning, and NLP to extract patterns from large and unstructured datasets; implement and back-test algorithms in high-quality code; document findings and collaborate with trading teams to deploy research-driven models.

Build high-performance tools and large-data research platforms to enable trading strategies. Work in small engineering teams to design systems, develop platforms and web frameworks, and apply techniques such as distributed computing, NLP, and machine learning to solve complex problems.

Lead product development of agentic merchandising optimisation: prototype and ship multi-agent systems, define trust and governance for agents on live experiences, productionize prototypes with safety/rollback/audit, partner across engineering, data science, experimentation and brand teams, and drive measurable conversion and revenue lift while preserving traveler trust.

Build high-performance, production-ready trading and research platforms in small teams. Design systems architectures, develop platforms and web frameworks, apply distributed computing, ML and NLP techniques, and collaborate on complex technical problems.

Work on research projects addressing security, privacy, and scalable systems. Tasks include engineering, data analysis, protocol design, open-source development, measurement, and implementation using systems languages. Projects may involve AI, distributed systems, privacy, or trusted execution. Interns matched to research directions, expected to communicate results and collaborate with teammates.

Own end-to-end product strategy, roadmap, and go-to-market for Expedia's bidding platform. Lead development of an autonomous bidding system, define decision logic and monitoring, partner with data scientists and engineers, establish metrics and operating cadences, and align stakeholders to drive scalable, auditable bidding automation across channels.

Conduct market microstructure research and develop quantitative models for equity algorithmic execution. Analyze large trading datasets, backtest methodologies, run A/B experiments, build analytics and data pipelines, validate production models, and collaborate with technology and client teams to industrialize research and produce client-facing materials.

Lead product ownership for Instruction Capture Client Data Exchange, managing a major institutional portfolio conversion. Translate client requirements into scope and business requirements across SWIFT, XML, FIX and CSV formats. Drive product vision, roadmap, AI-enabled validation and straight-through processing improvements, coordinate cross-functional delivery, manage testing and releases, and align stakeholders and data governance with the Chief Data & Analytics Office.

Lead AI-driven data and analytics programmes in financial services, mentoring teams and ensuring delivery of measurable outcomes.

Lead analytics and data-science work for Localization: design and run A/B and causal experiments, build and deploy ML/NLP/LLM models at production scale, create scalable SQL/Python pipelines and dashboards, translate multilingual insights for stakeholders, mentor peers, and co-own metric frameworks and decision workflows.

Develop, test, and deploy software solutions for automated trading systems in partnership with Quantitative Researchers. Implement high-performance, scalable systems using advanced quantitative techniques, distributed computing, ML/NLP, and strong software engineering practices. Collaborate on priorities, deliver custom solutions, and engage with senior team members during an 11-week internship.

11-week internship building high-performance research platforms and trading tools. Work in small teams on distributed systems, NLP/ML applications, and web frameworks while collaborating with senior engineers.

Conduct quantitative research and statistical analysis on crypto markets to develop, backtest, and implement automated trading strategies. Work with large and unconventional data sets to build valuation models, refine algorithms, and deploy signals in live trading to drive P&L growth.

As a Data Analytics Principal Consultant, you'll lead data transformation initiatives, mentor consultants, and engage with stakeholders in financial services to drive data literacy and innovation.

Lead bioinformatics strategy and execution across Discovery client engagements. Design and implement computational multi-omics workflows, translate biological questions into analytical frameworks, deliver client-ready insights, mentor junior staff, support business development, and help grow internal bioinformatics capabilities and thought leadership.

Lead and mentor an agile team to design, develop, secure, and operate scalable cloud-native applications using modern front-end tech and AI-assisted engineering practices; drive automation, code quality, resiliency, and operational stability.

Lead MGA pricing strategy using statistical techniques and machine learning. Build and maintain pricing models, monitor portfolio risk, recommend price adjustments, evaluate product profitability, create insights and dashboards, and mentor junior analysts while collaborating with underwriting and data science teams.

Lead product strategy and execution for an internal FinCrime and operations platform. Own customer risk data, intelligent case handling, and AI/automation foundations. Manage a 30-person multi-team squad, align cross-functional stakeholders, drive consolidation of tooling, and productize ML/LLM capabilities to scale compliance, reduce manual work, and lower cost-to-serve.

Design and deliver AI upskilling, awareness, and change initiatives across the Commercial & Investment Bank. Maintain an AI tool inventory, draft communications, track engagement and adoption, analyze gaps, and translate complex AI and regulatory topics into clear, practical materials to drive responsible AI use.

Lead credit analysis and modeling for securitized products, translate risk into actionable insights, prototype and scale analytical solutions using Python and automation, develop and validate credit loss models, design stress-testing frameworks, and collaborate with investment, risk, and technology teams to deliver governed, production-ready analytics.

Lead design and delivery of high-performance, real-time data pipelines and analytics for trading. Drive AI-enabled data engineering, mentor engineers, manage global initiatives, and improve SDLC, testing, and operational reliability.