Top Machine Learning Jobs in London

Analyzes complex datasets to identify unauthorized usage, revenue leakage, fraud indicators, anomalies, contractual non-compliance, and commercial opportunities. The role develops monitoring frameworks, dashboards, automated reporting processes, and investigative methodologies while partnering with intelligence, commercial, data science, product, and engineering teams to produce actionable revenue protection insights.

Provides engineering-led support for enterprise Azure customers, resolving complex escalations, conducting root-cause analysis, and improving customer solutions throughout their lifecycle. Designs, deploys, and troubleshoots cloud-native architectures, automation, APIs, telemetry, and operational tooling. Partners with engineering, product, and field teams to prioritize customer-impacting improvements, communicate technical issues, optimize deployments, and translate customer feedback into service reliability and product enhancements.

Support customer implementations, onboarding, process documentation, internal tooling, knowledge-base management, operational reporting, and product feedback analysis. Collaborate with Customer Success, Product, and Engineering to scope improvements, identify process gaps, automate workflows, monitor customer adoption and KPIs, and perform QA for feature releases.

Drive strategic outbound prospecting to engage enterprise brands, identify partnership opportunities, and generate qualified pipeline for Enterprise Account Executives. Customize outreach across calls, email, social selling, and campaigns; manage territories and account prioritization; use Salesforce and reporting tools to optimize performance; and contribute to process improvements, mentorship, and team initiatives.

Owns FICO’s strategic partner relationship across EMEA, driving joint revenue growth, pipeline development, sales campaigns, negotiations, and multi-million-dollar channel agreements. Builds C-suite relationships, develops multi-year engagement roadmaps, coordinates internal and partner teams, manages multiple sales engagements through close, and leads co-marketing and co-sales initiatives. Requires deep expertise in payments, banking, fintech, channel pricing, AI, decisioning, and partner ecosystem dynamics.

Owns FICO’s strategic partner relationship across EMEA, driving joint revenue growth, channel sales, multi-year engagements, and major contract negotiations. Builds C-suite relationships within the payments and fintech ecosystem, leads virtual sales and delivery teams, develops partner strategies and pipelines, and manages sales campaigns through close. The role also supports co-marketing, industry events, forecasting, and solution positioning across banking, payments, AI, machine learning, and decisioning markets. It requires regular onsite work in Basildon and London plus periodic US travel.

Analyze complex shipping datasets, create data sources, and build dashboards that communicate actionable insights. Translate client and business needs into analytical solutions, identify market trends and disruptions, and collaborate with product, data, engineering, and commercial teams. Use SQL and AI tools such as Claude Code, Copilot, and ChatGPT to accelerate analysis, automate workflows, improve reporting, and develop impactful analytics products.

Principal Solution Engineer responsible for helping UK customers evaluate and adopt Snowflake. Partners with sales teams, channel partners, and customers to present solutions, conduct demos and proofs of concept, design architectures, develop technical champions, and secure technical wins. Requires strong modern data, cloud, SQL, presentation, and customer-facing skills. The role also involves competitive positioning, partner collaboration, account planning, and representing Snowflake at industry events.

Support global markets by building and maintaining scalable data pipelines and datasets, partnering with traders and quants, improving data infrastructure and governance, diagnosing analytics issues, and translating technical outputs into clear insights for non-technical stakeholders.

Generate qualified B2B sales opportunities by following up inbound leads and targeted outreach. Conduct account research, org-chart identification, and high-volume outbound prospecting. Collaborate with Account Executives on campaign tactics, maintain CRM records, and support field marketing events.

Build and deploy production ML models for lodging ranking and personalization, from problem framing through feature engineering, model development, A/B testing, and monitoring. Collaborate with engineers, product, and analytics to measure impact, detect model degradation, and iterate on robust, explainable solutions at scale.

As a Senior Machine Learning Engineer, you will design, develop, and optimize ML solutions for enterprise customers, focusing on generative AI for improved content management. Collaborate with teams to ensure high-quality outputs and lead ML education efforts.

Lead data strategy and engineering for AD/ADAS: collect, sample, label, and curate large-scale vehicle and simulator data; build evaluation frameworks and scalable pipelines; analyze data to improve perception and planning models; collaborate across teams and mentor colleagues to deploy production-ready ML solutions.

As a Principal Engineer at M&S, you'll drive technical strategy, influence architecture, and mentor engineers while delivering on personalization, search, and machine learning features in collaboration with cross-functional teams.

Lead Citi's AI-First PDLC, defining enterprise capability models, process governance, and AI-enabled standards. Oversee process mapping, AI-augmented LEAN assessments, stakeholder engagement, and build a global team to ensure audit-ready, controlled, and optimized AI-enabled operations.

Lead technical strategy and architecture for personalization, search, and recommendation systems. Deliver scalable ML-powered features, mentor senior engineers, and improve engineering quality across cross-functional teams.

The Technical Account Manager will drive customer success, manage accounts, deliver onboarding and demos, and align engineering solutions with customer needs.

10-week on-site Data Science internship in London supporting data discovery, enrichment and analysis for quantitative research. Tasks include data blending, statistical analysis, exploratory data analysis, visualization, building tooling, and collaborating with data scientists to scale and automate data processes.

10-week London-based summer research internship applying mathematical modelling, ML/deep learning, optimisation and back-testing to extract predictive signals from financial time-series. Interns complete an independent research project with mentorship, present findings to senior management, and may be considered for full-time roles.

The Director of Colleague Data Science & Analytics will lead the global HR analytics function, driving innovative solutions to support decision-making and enhance the colleague experience.

Lead retention and revenue growth for a portfolio of UK and Western EMEA accounts. Build high-touch client relationships, run multi-quarter growth plans, surface performance insights, launch and optimize campaigns, drive upsell/cross-sell, coordinate cross-functional teams, maintain forecasting and reporting, and represent RZR in strategic sessions and in-person client engagements.

Provide clinical and translational expertise to prioritize clinical questions, interpret model outputs, advise on data and academic partnerships, and support pharma engagement for onco-immunology digital-twin and data-generation programs.

Lead Workday Compensation implementations and HCM transformations: run workshops, gather requirements, configure, test, deploy, lead workstreams, liaise with clients and teams, and apply Accenture/Workday methodologies and AI-enabled tools.

Manage the product lifecycle for network products, define roadmaps, gather customer feedback, and collaborate with teams to enhance user experience.

As a Product Manager, you will lead the lifecycle of real-time payments fraud prevention products, translating client needs into product specifications, and collaborating with ML experts and regional teams for successful implementation.