Top Machine Learning Jobs in London

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.

Analyse and optimise portfolio commercial performance, develop growth strategies, monitor client budgets and ROI, and identify market opportunities. The role partners with Sales, Marketing, Technology, and other teams to improve profitability and client satisfaction. Responsibilities include competitor analysis, digital marketing and monetisation analysis, process improvement, meeting leadership, presentations, and using Looker, machine learning, and AI tools to monitor performance and support strategic decisions.

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.

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.

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.

Develop and deploy production machine learning models for lodging search ranking, personalization, and recommendations. Lead end-to-end scientific work including problem formulation, data exploration, feature engineering, model development, experimentation, evaluation, and operationalization. Collaborate with engineering, product, analytics, and business teams on scalable systems, APIs, data modeling, and measurable business outcomes. Mentor teammates and advance recommender systems, retrieval, ranking, and generative AI capabilities.

Own the end-to-end lodging Search Results Page platform across Expedia, Hotels.com, and Vrbo. Define product vision, roadmap, requirements, experiments, and delivery plans while improving property discovery and evaluation. Lead search, AI, personalization, and property-card experiences across web and mobile. Collaborate with Engineering, Design, Analytics, Machine Learning, Brand, and business teams throughout the product lifecycle.

Leads full-cycle sales of Data and AI solutions, including data readiness assessments, modern data platforms, governance, analytics, and applied AI. Builds pipeline, develops customer relationships, manages proposals and negotiations, closes deals, and achieves revenue targets. Partners with Microsoft and other vendors, account teams, solution architects, and delivery teams to create transformation roadmaps and co-sell opportunities. Serves as a Data and AI subject matter expert while translating technical concepts into commercial value for strategic UK customers.

Leads customer-facing AI solution architecture, pre-sales engagements, use-case development, technical demonstrations, and end-to-end design of AI platforms, data pipelines, machine learning systems, and MLOps environments. Acts as an AI subject-matter expert connecting customers, sales teams, partners, and technical architects while supporting offering development, sales enablement, thought leadership, and team development.

Leads CDW’s UK Data & AI Solution Sales business, defining strategy, scaling data-readiness and AI propositions, growing revenue and profit, and managing customer, vendor, and partner relationships. The role oversees teams spanning data platforms, engineering, governance, analytics, and applied AI; develops go-to-market plans; ensures responsible, compliant solution selling; builds Microsoft and strategic vendor alliances; and drives talent development, forecasting, operational standards, and customer outcomes.

Design, develop, test, and improve low-latency electronic trading software supporting pricing, execution, risk management, and market connectivity. Translate business requirements into scalable technical solutions, define performance and reliability requirements, and partner with global stakeholders, traders, analysts, and project managers. Contribute to system architecture, test automation, development processes, and reliable software delivery across fixed income, currencies, commodities, and other trading domains.

Lead data science initiatives for KYC and customer onboarding, developing and managing machine learning systems for document verification. Responsibilities include creating image and tabular datasets, iterating on deep learning models, optimizing model performance, maintaining Python code, researching fraud prevention methods, collaborating with stakeholders, and mentoring junior data scientists.

Design and implement knowledge graph, semantic modeling, and advanced data solutions for financial services clients. Identify use cases for graph technologies, analytics, and AI; apply responsible AI workflows; explain complex approaches to stakeholders; and contribute to consulting practice growth through thought leadership, ecosystem development, and talent development.

Lead product analytics for customer onboarding and account access. Derive insights from data, guide product decisions, partner with product managers, engineers, and designers, and identify opportunities to improve customer experience while preventing fraud. Build data pipelines, dashboards, and KPI reporting systems; communicate findings across teams; and explore AI-driven automation and machine learning techniques to improve analytics and generate insights.

Lead product analytics for Wise’s Send tribe, focusing on verification, transfer predictability, service quality, customer retention, and growth. Analyze customer problems, define KPIs, conduct A/B tests and causal analyses, track product impact, and guide prioritization with Product Managers and stakeholders. The role also supports scaling service operations, improving customer journeys, and identifying opportunities through SQL and Python analysis, with optional use of Airflow, dbt, Looker, and predictive modeling.

Lead the definition and design of Cloudflare’s Web Integrity and Trust product suite. Create coherent experiences for configuration, navigation, traffic investigation, analytics, and value demonstration in complex, probabilistic security systems. Work across product managers, engineering, and leadership to develop a 0-to-1 interaction model, make sophisticated data understandable, and establish design processes as the first embedded design lead. The role emphasizes interaction design, information architecture, data visualization, prototyping, and AI-assisted product development.

Lead the architecture and production deployment of deep learning and machine learning systems for real-time financial crime detection. Design sequence-based, graph-based, and attention-based models; establish reusable experimentation-to-production pipelines; evaluate foundation models and embeddings; make architecture decisions under latency and throughput constraints; partner with data scientists on evaluation and measurement; and mentor engineers and data scientists.

Lead development and deployment of machine learning and Generative AI systems for AML operations. Responsibilities include building EDD LLMs, evaluation datasets and automated testing frameworks, prompt optimization, shadow testing, production monitoring, human-in-the-loop workflows, and financial crime prevention solutions. The role also provides technical leadership, mentorship, architectural guidance, and cross-functional collaboration.

Leads cybersecurity architecture for cloud-based applications and enterprise systems. Defines target architecture, identifies and mitigates risks, automates recurring remediation, evaluates emerging technologies and vendors, and drives AI-assisted security validation across SDLC toolchains. Collaborates with technical teams and senior business stakeholders while ensuring security, resiliency, auditability, and data-sensitivity requirements are met.

Develop and deploy machine learning and generative AI solutions for payments and banking operations. Build LLM-powered workflows, evaluation frameworks, ML services, and production deployment pipelines. Apply MLOps practices including monitoring, testing, versioning, governance, and rollback. Collaborate with product, risk, operations, and technology teams while documenting models, communicating results, and ensuring secure, reliable, and compliant production systems.

Lead data science for Wise’s AML Risk team by developing machine-learning and GenAI detection systems, optimizing precision-recall tradeoffs, building coverage frameworks, and deploying production Python services. Hire and mentor specialists, collaborate with product, engineering, and operations teams, design model evaluation experiments, improve operational processes, and create investigator insights for detecting financial crime across global transactions.

Leads development of secure, scalable data platforms supporting batch, streaming, ML, and LLM workloads. Designs distributed data systems using Spark, Ray, Kafka, Iceberg, and OpenSearch; productionizes model training, deployment, monitoring, and lifecycle management; and builds governed LLM solutions. Provides technical leadership, code review, incident response, vendor evaluation, responsible AI guidance, automation, and mentorship across engineering teams.

Drive product and business impact through statistical modeling, experiment design, Bayesian marketing analysis, machine learning, NLP, LLM applications, and classifier implementation. Build growth metrics, monitoring pipelines, evaluation datasets, and AI trigger systems across search and Duck.ai. Analyze privacy-constrained data, deploy production-grade models, optimize SQL queries, and lead complex projects from scoping through production with minimal direction.

Develop machine learning models and computer vision algorithms for photon-efficient, event-driven imaging in AR glasses. Responsibilities include tracking, depth estimation, SLAM, detection, probabilistic modeling, and novel imaging algorithms for ultra-low-light, high-temporal-resolution systems. The role requires collaboration with global hardware and software teams and emphasizes fast, reliable implementation in C++ and Python.

Develop and deploy computer vision and machine learning algorithms for photon-efficient, event-driven imaging in next-generation AR glasses. Responsibilities include tracking, depth estimation, SLAM, detection, probabilistic modeling, and ultra-low-light imaging. The role requires close collaboration with global hardware and software teams and focuses on creating fast, robust, and accurate solutions for wearable devices.