Top Machine Learning Jobs in London

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.

Leads cybersecurity architecture, assessments, threat modeling, technical risk evaluations, and secure software development practices across cloud, AI/ML, mobile, and enterprise technology domains. Develops security reference architectures, advises technology and business teams, evaluates controls, influences design decisions, and oversees security implementation priorities and deliverables. Serves as a cybersecurity subject matter expert while mentoring and partnering with stakeholders to address regulatory, risk, and technical security requirements.

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

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.

Analyzes, configures, integrates, migrates, and tests telecom BSS, OSS, cloud, and legacy systems. The role supports product introductions, upgrades, capacity changes, automation, scripting, DevOps, data pipelines, and customer acceptance testing. It also provides post-project technical support, continuous improvement, technical assessments for pre-sales, and knowledge sharing. Candidates need telecom vendor or operator experience, BSS architecture knowledge, Linux, networking, databases, mobile technologies, charging systems, automation tools, and analytics platforms.

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.

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 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.

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.

Build and operate scalable full-stack systems that prevent fraud, account takeovers, scams, and financial crime. Own projects end to end, develop customer-facing security controls, improve transaction monitoring and detection capabilities, and collaborate with Product, Design, Data Science, and Investigations. The role requires Java or JVM expertise, Spring, modern frontend development, distributed systems, databases, CI/CD, testing, strong product judgment, and mentoring junior engineers.

Design, develop, and maintain secure, scalable software solutions as a seasoned agile team member. Produce high-quality production code, architecture/design artifacts, data visualizations, and troubleshooting. Use CI/CD, resilient application patterns, enterprise AI-assisted development tools, and validate AI outputs. Contribute to engineering communities and improve code hygiene and system architecture.

Leads Remitly’s global transaction monitoring program, owning policy, standards, coverage methodology, scenario strategy, tuning, model governance, regulatory change, and assurance. The role identifies coverage gaps, drives remediation, defines effectiveness metrics, supports new products and payment rails, and represents the program to regulators, auditors, and partner banks. It also builds and develops teams while partnering with Data Science, Engineering, Product, Operations, and regional compliance leaders.

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.

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.

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.

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.

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.

Develop and deploy statistical, machine learning, mathematical, and optimization models for Prime Finance. Responsibilities include forecasting borrow rates and demand, optimizing pricing and inventory allocation, researching alpha signals and hedging strategies, building analytics infrastructure, managing model risk, and communicating results to trading, technology, risk, and senior stakeholders. The role also mentors junior researchers and documents methodologies.