Top Machine Learning Jobs in London

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.

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.

Leads enterprise and portfolio architecture for Commercial Banking and international technology domains. Defines target-state architecture, modernization and AI strategies, governance standards, technology roadmaps, resiliency and risk controls, and investment priorities. Advises CIOs and senior stakeholders, manages engineering leaders, drives cross-functional initiatives, develops talent, and oversees secure, scalable technology solutions. The role requires substantial executive influence, architecture expertise, regulatory awareness, and experience governing enterprise AI solutions.

Leads the strategy, roadmap, development, and performance of risk tooling products supporting control assurance, audit readiness, risk reporting, and operational risk management. Drives automation of manual risk and controls processes, partners with Engineering, Risk, Audit, Controls, and Architecture teams, establishes governance for complex initiatives, and advances enterprise analytics and AI-enabled risk solutions. Coaches product teams, manages stakeholders, monitors market trends, and ensures product investments deliver measurable business outcomes.

Supports EMEA data governance and risk management across asset and wealth management. Responsibilities include maintaining governance standards, coordinating forums, investigating policy breaches, tracking remediation, supporting data protection activities, improving processes, managing workstreams, reporting metrics, and coordinating regulatory requirements. The role partners with Risk, Compliance, Legal, Audit, Technology, data owners, and senior stakeholders while identifying opportunities to use AI and automation.

Leads a data science and AI/ML team supporting risk management and compliance. Oversees predictive models, LLM solutions, autonomous agents, and enterprise AI applications from design through deployment and monitoring. Partners with Product, Business, and Engineering teams to embed AI into workflows, improve operational efficiency, and deliver business value. Ensures model risk management, responsible AI, explainability, fairness, governance, drift monitoring, and retraining. Mentors teams, communicates insights to senior leadership, and guides research, experimentation, and innovation.

Design and deliver enterprise-grade machine learning systems and AI-powered applications for banking. Build scalable, secure, distributed applications and automated cloud, desktop, and ML pipelines. Apply MLOps practices for versioning, reproducibility, and observability while collaborating with cloud and site reliability engineering teams. Develop reusable libraries and business-critical, data-intensive solutions, aligning machine learning problems with business objectives. The role may include mentoring or people leadership.

Lead research, design, and evaluation of large-scale detection models for automated, fraudulent, and malicious activity. Define measurement frameworks for noisy or incomplete ground truth, mentor data science practitioners, advance AI/ML techniques, and shape long-term detection strategy. Partner with ML Engineering, Data Engineering, and Product teams to influence roadmaps and protect Cloudflare customers from evolving threats.

Lead an applied AI team building and deploying agentic automation for banking operations. Own shared AI capabilities, orchestration, evaluation, and human-agent workflows while directing end-to-end production delivery under governance. Mentor AI engineers, establish technical direction, align cross-functional teams, manage senior stakeholders, and measure agent autonomy and human involvement. The role requires hands-on AI engineering, production agentic systems experience, strong software engineering foundations, and leadership in complex regulated environments.

Leads Wise’s global Servicing Scale organization, covering workforce management, demand and performance management, capacity planning, and internal tooling. Owns operational planning automation, technical standards, global budget and headcount, outsourcing strategy, and product roadmaps for workforce and capacity systems. Builds scalable, data-driven infrastructure using AI and predictive modeling while developing senior leaders, influencing executives, and ensuring servicing operations can support rapid customer growth without proportional cost increases.

Lead development of secure, high-performance, low-latency cloud-based payments applications using Java and AI-assisted engineering practices. Responsibilities include designing and coding payment flows, reviewing and debugging code, establishing secure coding and automated testing standards, supporting production stability, coaching engineers on responsible AI adoption, evaluating architectures, and promoting modern software engineering practices across the organization.

Lead analytical data science for Wise’s customer support organization. Measure service quality, diagnose root causes, design metrics, evaluate interventions, and use experiments, causal inference, machine learning, NLP, and LLM techniques to improve customer outcomes. Partner with Product, Design, Operations, and Engineering to guide automation strategy, prioritize opportunities, and influence product and business decisions using customer, conversational, and operational data.

Develop and deploy AI and machine learning solutions for workforce analytics. Conduct statistical analyses, experiments, and model evaluations; build scalable model factories and evaluation frameworks; apply generative AI and agentic development approaches; collaborate with business, product, and technology teams; communicate insights; and ensure compliance with risk, control, and governance requirements.

Develop and deploy production AI and machine learning solutions for Markets Operations, including process automation, anomaly detection, document intelligence, workflow optimization, and generative AI. Responsibilities include model development, MLOps, performance monitoring, dataset analysis, stakeholder collaboration, documentation, and continuous improvement of AI-driven business tools.

Off-cycle quantitative research intern supporting systematic trading, financial engineering, statistical modeling, portfolio optimization, and derivatives pricing. Responsibilities include developing mathematical models and algorithms, valuing and hedging transactions, conducting alpha research, calibrating models, optimizing pricing, managing portfolio risk, and collaborating with traders, technologists, sales, and risk teams. Candidates gain hands-on global markets experience and may be considered for full-time employment after successful completion.

Own the strategy and roadmap for AI-powered fraud investigation automation. Lead discovery, prioritization, production rollout, evaluation, governance, monitoring, and continuous improvement. Partner with Engineering, Data Science, Design, Operations, Risk, and Compliance to combine deterministic logic, machine learning, GenAI, human oversight, and operational processes into scalable, safe, compliant fraud solutions.

Develop and deliver production AI/ML solutions across the full lifecycle using Agile methodologies. Translate business requirements into technical specifications, build secure production code and algorithms, create architecture artifacts, analyze large datasets, develop visualizations, troubleshoot systems, and identify improvements. The role requires expertise in machine learning, Python, Spark, distributed computing, AI frameworks, agentic workflows, and AWS services, while contributing to engineering communities and emerging technology initiatives.

Lead data science for Wise’s cross-border transfer pricing strategy. Design pricing experiments, apply causal inference, model price elasticity and revenue impacts, optimize prices across customer segments, and build automated reporting and data infrastructure. Use machine learning to analyze pricing-related customer contacts, identify customer pain points, and deliver insights to Product, Operations, Finance, Commercial, and senior leadership.

Lead technical strategy, architecture, and delivery for a large-scale risk analytics and reporting platform. Design scalable Java and React-based applications, govern frontend architecture and design systems, integrate enterprise platforms and data sources, and drive reliability, resiliency, observability, security, and compliance. Partner with Risk, Product, Data, Architecture, and Engineering stakeholders while evaluating AI, machine learning, and generative AI capabilities for analytics, automation, and decision support.

Lead Wise’s AI Assistant and route-by-route customer activation strategy. Own conversational banking experiences, agentic AI development, global product frameworks, funnel optimization, experimentation, and customer insights. Partner with engineering, design, analytics, regional, compliance, payment operations, and vendor teams to improve first-transfer conversion and scale personalized cross-border payment experiences globally.

Build and deploy practical machine learning, deep learning, and generative AI solutions. Design and evaluate experiments, work with large language models and AI agents, write production-quality code, optimize model performance, and collaborate with product and engineering teams to deliver scalable AI systems.

Deliver enterprise and operational risk transformation and advisory services for financial institutions. Assess and improve risk processes, controls, governance, market abuse frameworks, and trade surveillance. Support AI-enabled analysis, surveillance model tuning, workflow automation, validation, auditability, and responsible AI practices. Collaborate with business, technology, compliance, and risk stakeholders to identify control gaps and deliver data-driven improvements.

Partner with large UK private-sector clients from early ideation through production planning. Provide technical advocacy, solution design, validation project management, best-practice guidance, and expertise across networking, cybersecurity, edge computing, Internet performance, and Cloudflare technologies. Explain complex concepts and ROI, support customer buying decisions, collaborate with internal specialists, and contribute to technical knowledge sharing. The role includes significant in-region travel to customer offices, conferences, and events.

Own MGA portfolio risk and technical pricing analysis, maintaining statistical and machine-learning pricing models using Python, R, SQL, and specialized pricing tools. Identify market trends, recommend price adjustments, assess new product profitability, create underwriting dashboards, and communicate insights to business partners. The role also includes mentoring junior analysts and collaborating with underwriting and data science teams.

Develop and productionize generative AI products and augmented reality Lenses focused on image and video generation, editing, and LLMs. Build diffusion and flow-matching pipelines, evaluate open-source models and third-party APIs, and rapidly ship consumer-facing solutions. Collaborate with Product, Engineering, Lens Content, and Data Science teams to prototype, integrate, monitor, and improve models using A/B testing and user feedback. Lead complex technical initiatives while staying current with machine learning research.