Top Machine Learning Jobs in London

Lead architecture and delivery of scalable Android search and recommendations experiences. Set technical direction, design systems and APIs, integrate AI/ML, mentor mobile engineers, and collaborate with product and design to drive mobile strategy.

Develop and deploy analytics and AI-driven applications for private markets, especially private credit. Partner with investment, product, risk, and engineering teams across the investment lifecycle, including fundraising, portfolio construction, due diligence, monitoring, liquidity modeling, forecasting, and risk analysis. Translate complex financial analytics into scalable investment workflow solutions while managing projects, coordinating stakeholders, and communicating insights clearly.

Develop and deploy consumer-facing machine learning products and augmented reality Lenses focused on image and video generation, editing, and large language models. Build generative AI pipelines using diffusion and flow-matching models, integrate models and APIs into production, conduct A/B testing, evaluate open-source and third-party solutions, and collaborate with product, engineering, content, and data science teams.

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.

Build and improve fraud prevention and account integrity systems protecting customers from account takeovers and financial crime. Develop backend services and frontend features, design and operate CI/CD pipelines, and work with distributed and concurrent systems. Optimize relational and non-relational databases, apply test-driven development, and own projects end to end with a customer-focused, data-driven mindset. Collaborate with Product, Data Science, and Investigations teams; machine learning lifecycle experience is beneficial.

Leads analytics, AI, and machine learning strategy and delivery for Payments, including scalable data products, model lifecycle management, governance, and Generative AI initiatives. Partners with business, technology, quantitative research, and product teams to optimize liquidity, deposits, balance sheets, and revenue. Drives stakeholder adoption, self-service analytics, AI literacy, regulatory compliance, and measurable business outcomes.

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.

Design, develop, and deploy software solutions for automated trading systems while collaborating with researchers on technology priorities.

Lead TIDAL's product and brand design vision, drive complex end-to-end design initiatives, define systems and standards, pioneer AI-driven design, partner with Product/Engineering/ML, mentor designers, and identify new business opportunities to elevate artist-focused products.

Lead development of the label integrity layer for Risk ML: ensure label quality, define statistical metrics, build automated audits, monitor label drift, and work end-to-end on model training, evaluation, and deployment in collaboration with Risk Intelligence, Data Engineering, and Product teams.

Lead technical design and development of AI-native systems for credit pre-trade markets. Build scalable AI platforms, modernize legacy systems, deliver secure production code, partner with trading and product teams, support production operations, evaluate vendors, and drive engineering best practices and communities of practice.

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.

Senior front-end engineer on an agile Equities Sales & Trading team delivering secure, scalable cloud-native applications. Provides technical leadership, writes and reviews production code, drives design decisions, optimizes UI performance for high-frequency data, and advocates firmwide engineering practices and tools.

Lead development of cloud-native Python applications for global commodities trading desks. Design, build, test, and operate resilient, secure production systems; drive automation and CI/CD; evaluate vendor solutions; and mentor engineering communities of practice.

Build AI/ML-driven analytics and automation for CIB Treasury, Securities Services and Payments. Develop scalable data architecture, automate manual processes, create sequential decision-making tools to optimize net interest income, drive projects end-to-end from prototype to production, present commercial recommendations to stakeholders, and collaborate across Quant Research, Treasury, CIO, Technology and CDAO.

Lead and deliver secure, scalable post-trade software solutions. Design, develop, review, and troubleshoot production code; drive architecture evaluations; automate remediation; promote CI/CD, resiliency, and cloud-native practices; mentor engineering communities and collaborate with vendors and internal teams.

Lead development and adoption of information architecture standards, controlled vocabularies, and governed data models. Collaborate with business and technical teams to evaluate technologies, provide technical guidance, influence product design, and standardize operational and analytical data management across the Corporate Investment Bank.

Design, develop and optimize a large-scale Monte Carlo engine for CVA/FVA calculations; implement numerical techniques for efficiency; build production-grade analytics; collaborate with traders, risk managers and tech teams; drive software engineering best practices.

Lead execution of Client360 transformation initiatives by partnering with product, engineering, and business teams. Drive process improvement, data-driven insights, AI-enabled solutions, stakeholder engagement, KPI tracking, change management, and operational adoption to deliver measurable business value and regulatory-compliant outcomes.

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 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.

As a Lead AI Engineer, you'll architect and deploy generative AI systems, optimize large models, and lead teams in AI engineering across financial services.

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.

Lead analytics for the Financial Crime Platform, partner with product and engineering to build metrics, pipelines, visualisations, and features for fraud/AML risk models, drive discovery and data-driven decisions balancing risk and customer experience.