Top Machine Learning Jobs in London

Design and build real-time liquidity observability infrastructure and high-throughput streaming data pipelines for global financial operations. Architect Kafka and Flink systems, implement reliable event processing, real-time aggregation, streaming data models, and sub-second analytical querying. Partner with product, data science, quantitative analysis, and treasury teams while addressing latency, resilience, regulatory, and financial trade-offs. Develop well-tested systems supporting liquidity attribution, cash positioning, transaction routing, and ML forecasting.

Own the strategic vision and roadmap for Expedia Group’s sponsored listings auction platform. Lead auction mechanics, bidding, pricing, ad relevance, and optimization initiatives to improve traveler experience, partner ROI, marketplace efficiency, and revenue. Partner with engineering, machine learning, data science, and business teams to deliver technical products, define metrics, analyze performance, and use experimentation and AI tools to guide decisions. Communicate strategy and results to senior stakeholders while driving innovation in digital advertising and marketplace technology.

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.

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.

Own technical roadmaps and deliver scalable backend systems for KYC and onboarding verification. Design microservices, APIs, integrations with risk and compliance systems, and reliable customer-facing infrastructure. Lead large, complex technical projects, address scalability and security concerns, optimize databases, solve ambiguous problems, and mentor engineers while supporting regulatory compliance and customer experience.

Own the full enterprise sales cycle across EMEA and the US, from outbound prospecting and account planning through negotiation, procurement, closing, and account expansion. Sell content syndication and intent-led demand-generation programs to B2B marketing and revenue leaders. Build net-new pipeline, manage complex multi-stakeholder deals, meet revenue targets, maintain accurate forecasts, and collaborate with delivery, data, media, marketing, and client success teams.

Own Wise’s global paid search strategy and execution across Google Ads, Microsoft Ads, and Apple Ads. Set channel plans, KPIs, budgets, forecasts, bidding and optimization strategies; lead experimentation across ads and landing pages; improve reporting, attribution, automation, and AI-enabled capabilities; and evaluate emerging search channels. Partner cross-functionally with SEO, Product, Analytics, and Paid Marketing teams while mentoring colleagues and raising team expertise.

Lead the strategy, roadmap, and delivery of Wise’s graph risk intelligence platform. Define capabilities for connected-data ingestion, storage, computation, signal generation, modeling, analytics, and serving. Partner with engineering, machine learning, data science, and operational teams to accelerate experimentation, improve risk decisions, manage technical trade-offs, and drive platform adoption across financial crime, underwriting, support, finance, and customer relationship teams.

Lead development and deployment of Generative AI, LLM, and agentic AI systems for AML operations. Responsibilities include building evaluation frameworks, optimizing prompts, designing human-in-the-loop workflows, conducting shadow testing, monitoring model drift, deploying Python services, reducing financial crime risk, and mentoring data scientists. The role requires collaboration with AML subject matter experts and ownership of technical strategy across AI automation initiatives.

Lead development, governance, validation, deployment, and monitoring of fraud and identity-verification machine learning models. Evaluate vendor solutions, prepare model risk management documentation, address validation findings, investigate performance drift, maintain audit-ready evidence, and communicate model trade-offs to senior stakeholders and governance committees. Support regulatory compliance, audits, remediation, and downstream user training while partnering across technology, product, legal, compliance, and business teams.

Leads Expedia B2B’s analytics organization, managing analytics managers and senior analysts while shaping multi-year analytics roadmaps and business strategy. Partners with senior stakeholders to drive measurable outcomes, guides statistical and machine learning applications, establishes analytics engineering and visualization practices, develops talent, and collaborates with data engineering, product, and machine learning teams on scalable solutions.

Lead development and lifecycle management of machine learning models supporting KYC, onboarding, and document verification. Responsibilities include creating image and tabular datasets, developing deep learning models, optimizing performance, maintaining Python code, researching fraud prevention techniques, collaborating with cross-functional teams, communicating data science impact, and mentoring junior team members.

Own the roadmap for Expedia’s personalization platform serving cold-start, new, and anonymous travelers. Translate customer and business needs into platform requirements, prioritize backlogs, and partner with engineering, data science, design, analytics, marketing, and product teams. Lead experimentation and measurement while balancing relevance, privacy, fairness, explainability, latency, scalability, and business outcomes. Improve adoption, personalization quality, platform performance, and decision visibility across partner products.

Provides second-line oversight of Wise’s global AML and CTF framework, including transaction monitoring, investigations, enhanced due diligence, governance, risk assessments, control effectiveness, regulatory compliance, and financial crime reporting. Advises Product, Compliance, and Operations teams, reviews systems and controls, leads remediation and effectiveness reviews, supports training, and contributes to global AML/CTF strategy and governance.

Lead Wise’s Risk Modelling ML Engineering pillar for financial crime detection. Architect model factories, experimentation pipelines, deployment infrastructure, automated retraining, drift detection, threshold management, monitoring, and audit trails. Recruit and develop a senior ML engineering team while setting technical standards, architecture, and engineering culture. Partner across platform teams and guide systems spanning deep learning, production infrastructure, high-throughput inference, and model lifecycle automation.

Develop AI/ML-driven analytics, automation, data architectures, and sequential decision-making tools for Securities Services. Responsibilities span data processing, quantitative modeling, prototype-to-production development, balance-sheet and deposit optimization, visualization, and stakeholder presentations. The role collaborates with Quantitative Research, Technology, and data teams to solve complex commercial problems using machine learning, large language models, and cloud or HPC environments.

Lead and scale a second-line technology risk assurance function for a regulated fintech. Manage assurance across IT controls, cloud infrastructure, IAM, CI/CD, APIs, databases, business continuity, and AI systems. Build automated control testing and remediation workflows using Python, SQL, AI agents, and continuous monitoring. Lead a technical assurance team, engage auditors and regulators, and communicate technology risk to engineering leaders, executives, and board-level committees.

Build and operate scalable backend and frontend systems that prevent account takeovers, scams, and financial crime. Own projects end to end, develop real-time detection and prevention controls, improve automation, and protect customer funds. Responsibilities include Java or JVM backend development with Spring, React-based frontend work, distributed systems, CI/CD, database design and optimization, testing, and collaboration with Product, Data Science, and Investigations teams.

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.

Lead Wise’s Verification Platform engineering team, managing and mentoring engineers while owning the technical roadmap, architecture, reliability, security, scalability, and operational excellence of business KYC infrastructure. Partner with global product and engineering teams, contribute hands-on when needed, run engineering rituals and incidents, and guide development of configuration-driven rules, review tooling, vendor integrations, distributed decisioning, and event-driven re-evaluation systems.

Owns the full sales cycle for Data and AI solutions, from customer discovery and data-readiness assessments through proposals, negotiation, and close. Develops pipeline, sells modern data platforms, governance, analytics, cloud, and applied AI services, and builds relationships with strategic technology decision-makers and Microsoft partners. Translates technical capabilities into business outcomes, supports bids and tenders, forecasts accurately, and drives follow-on transformation and AI adoption.

Manage and expand strategic partner alliances for SailPoint’s enterprise software business. Develop joint business, marketing, technical certification, and go-to-market plans; generate partner-sourced pipeline; coordinate account mapping, co-selling, enablement, promotions, and implementation capacity. Serve as the primary liaison between SailPoint and partner organizations, monitor performance and KPIs, ensure compliance and delivery quality, and present quarterly business assessments. The role requires extensive enterprise partner-management experience, analytical skills, executive communication, and approximately 50% travel.

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.

Leads AI transformation, governance, quality oversight, risk management, and responsible adoption across Pfizer Global Supply and QSEO. Establishes GxP-compliant AI lifecycle practices, inspection-readiness frameworks, governance forums, portfolio monitoring, inventory management, metrics, and reporting. Advises senior leaders on AI regulations, deployment risks, investment priorities, and compliance while leading cross-functional initiatives and influencing stakeholders across Quality, Digital, Operations, and R&D.

Leads Airwallex’s global sanctions compliance strategy, second-line governance, screening oversight, regulatory engagement, and technology modernization. The role manages complex sanctions escalations, regulatory examinations, disclosures, geopolitical risk monitoring, and AI-enabled screening initiatives across global payment operations. It also reports programme risk to executives and the board while scaling a cross-regional sanctions team.