Top Machine Learning Jobs in London

Lead the architecture, development, deployment, monitoring, governance, and continuous improvement of production-scale machine learning platforms. Establish MLOps standards, feature stores, data quality frameworks, testing strategies, explainability practices, and observability. Build low-latency inference services, oversee AWS SageMaker workflows, guide validation and experimentation, solve reliability and scaling challenges, and coach engineers while driving technical direction.

Lead Field’s quantitative analysis function for battery storage and renewable energy assets across European power markets. Own pricing, valuation, risk, systematic trading, and battery spread-option models; oversee volatility, hedging, back-testing, scenario analysis, VaR, and CFaR reporting. Support structured product origination, market entry, and commercial pricing while managing market data infrastructure, ETRM implementation, model governance, and a junior quantitative professional.

Conduct quantitative research and statistical analysis on crypto markets to develop, backtest, and implement automated trading strategies. Work with large and unconventional data sets to build valuation models, refine algorithms, and deploy signals in live trading to drive P&L growth.

Build Paddle’s data science function and production decisioning systems from the ground up. Prioritize high-value use cases, personally deliver the first ML or agentic system, and own deployment, monitoring, experimentation, reliability, governance, and financial impact. The role will establish the production ML stack, collaborate across Product, Engineering, Risk, Finance, and Compliance, then hire and lead data scientists and ML engineers. Experience with regulated transactional domains, production ML operations, experimentation, and executive stakeholder management is required.

Lead end-to-end delivery of complex Industrial AI and digital transformation projects, from kickoff through deployment, adoption, and value realization. Own scope, schedules, budgets, quality, financial performance, risks, governance, and customer outcomes. Partner with technical teams and executive stakeholders, manage steering committees, facilitate value realization workshops, support change management and training, and identify expansion opportunities. Apply PMO methodologies and continuous improvement practices across enterprise software and industrial technology implementations.

Research, design, and develop algorithms and software systems for AI-driven CNC machining, including toolpath optimization, cutting strategies, and automated CAM workflows. Collaborate with manufacturing experts, data scientists, and software engineers to convert advanced concepts into reliable production software. The role emphasizes high-performance C++ development, computational geometry, numerical methods, optimization, and modern software engineering practices.

Lead the research, design, productionization, and scaling of machine learning models for pricing and shipping optimization. Own high-impact projects, conduct rigorous experiments, apply causal inference and optimization techniques, collaborate with engineers and cross-functional stakeholders, communicate findings, and mentor junior team members.

Lead product efforts to detect money laundering and related fincrime by building hyper-targeted, region-specific detection systems using machine learning and LLMs. Work with compliance, data scientists, engineers, designers and ops to define vision, roadmap, and measurable metrics (AML Recall and SAR Cost) while satisfying global regulatory requirements and improving automation and precision.

Lead complex customer deployments of physical AI and robotics systems from prototype through production. Coordinate software, AI, hardware, infrastructure, operations, and customer teams; manage milestones, dependencies, site readiness, testing, validation, logistics, launches, risks, and technical blockers. Partner with enterprise customers, establish scalable deployment and release processes, and define approaches for scaling systems across diverse environments.

Leads the global AI, automation, data, and integration strategy for Professional Services. Builds a specialist team, identifies automation opportunities across delivery, establishes scalable implementation frameworks, improves cost-to-serve and time-to-value, and uses data-driven insights to optimize performance. Partners with Sales, Product, R&D, and delivery leadership on solution design, integration strategy, operational transformation, and adoption of emerging technologies.

Leads strategic AI and machine learning initiatives from concept through production. Designs scalable solutions connecting data, models, platforms, and systems; develops reusable engineering patterns; improves solution quality and reliability; conducts analysis supporting strategic decisions; builds stakeholder partnerships; and provides organizational leadership, mentoring, and innovation across the enterprise.

Designs and delivers enterprise-grade AI solutions using machine learning and generative AI. Partners with Product, Sales, Trading, and Operations to build scalable technology solutions. Applies modern AI frameworks and AI-assisted software development practices across design, development, testing, documentation, and support. Leads engineering best practices, automation, continuous improvement, and innovation within agile teams, using strong Java and Python skills in mission-critical environments.

Designs and delivers enterprise-grade AI solutions, including machine learning and generative AI applications, using Java and Python. Partners with Product, Sales, Trading, and Operations to build scalable technology solutions. Advances AI-driven software development practices across design, development, testing, documentation, and operational support while improving engineering productivity, quality, and delivery through agile collaboration.

Leads operational support for production AI solutions, including monitoring, incident management, defect remediation, enhancements, deployments, governance, and performance evaluation. Coordinates internal teams and third-party AI engineers, maintains support processes and documentation, and monitors reliability, accuracy, drift, bias, fairness, cost, and business value. Partners with data, technology, governance, and business stakeholders to ensure AI solutions remain stable, compliant, effective, and aligned with evolving needs.

Deliver technical client deployments of the OneView platform, including data extraction, engineering, data science, cohort development, dashboards, predictive models, and analytics. Manage technical project delivery, stakeholder communication, benefits tracking, client training, testing, and platform improvements. Work with consulting, governance, product, and QA teams to translate client data into actionable insights and measurable social impact.

Designs, develops, and deploys production-grade machine learning systems focused on LLMs, Generative AI, and deep learning. Responsibilities include building scalable ML libraries and research workflows, optimizing distributed training and inference, improving experiment tracking and model lifecycle management, and bridging research prototypes with robust implementations. The role requires collaboration with data science and platform teams, strong software engineering practices, cloud and MLOps expertise, and mentoring across the technical team. Biomedical, clinical, or omics data experience is preferred.

Organize and maintain sales playbooks, battlecards, objection-handling guides, and competitive content. Design onboarding and ramp programs, deliver ongoing sales coaching, identify training gaps, and coordinate content development with instructional designers. Manage enablement content and adoption within Docebo, using usage data to improve effectiveness. Partner cross-functionally with Sales, Marketing, and Product in a B2B SaaS environment.

Summer internship on the Global Data Science team to develop and optimize time-series forecasting models (ARIMA/SARIMA, XGBoost, LSTM). Support end-to-end data ingestion, back-test datasets, collaborate with traders and analysts, and conduct ad hoc research on energy fundamentals and analytics trends.

Build and productionize forecasting and machine learning models using weather, climate, and satellite data to generate agricultural, environmental, and risk signals. Own end-to-end pipelines from data ingestion and modeling through evaluation, orchestration, and customer delivery. Improve experiment design, uncertainty analysis, reproducibility, and monitoring while collaborating with science, engineering, product, and market intelligence teams.

Build and deploy production-grade machine learning software, tools, infrastructure, and scalable reusable solutions. Collaborate with engineers, data scientists, commercial leads, clients, and partners to solve complex challenges. Lead technical scoping, architecture, ML deployment standards, and customer advisory activities while translating technical concepts for non-technical stakeholders.

Build and deploy production-grade machine learning software, tools, infrastructure, and scalable solutions. Collaborate with engineers, data scientists, commercial leads, clients, and partners to solve complex challenges. Lead technical scoping, architecture decisions, and ML deployment standards while advising technical and non-technical stakeholders on production AI systems.

Leads positioning, messaging, go-to-market strategy, launches, sales and channel enablement for Sophos AI cybersecurity solutions. Develops category narratives, launch assets, competitive intelligence, analyst relationships, customer feedback programs, and partner enablement. Collaborates cross-functionally with product management, research, sales, marketing, and channel teams to translate technical capabilities into differentiated market stories and pipeline outcomes.

Lead and mentor a data science team building ML and LLM solutions for cybersecurity. Translate business needs into research and production ML objectives, prioritize roadmaps, collaborate cross-functionally, and drive technical vision, model development, and operationalization for malware detection and threat analysis.

Lead a global KYC, name screening and transaction monitoring operations team. Define strategy, staffing and 24/7 coverage, drive AI/automation transformation, improve procedures and controls, balance risk with customer experience and commercial impact, and partner with Risk Product, Engineering and 2LOD to scale onboarding and FinCrime operations.

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.