Top Machine Learning Jobs in London

Lead product definition, backlog and roadmap for Intelligent Risk Capture and Digital Services. Bridge business stakeholders and delivery teams through the full SDLC, own technical IP and standards, support client deployments and customisations, run agile ceremonies, monitor performance, and drive continuous, data-driven product improvements.

Lead the data science organization to deliver AI products, mentoring teams and executing a strategic vision for machine learning applications.

Join iSAM Vector as a Quantitative Researcher to design, test and implement systematic trading signals across global markets. Responsibilities include signal research, backtesting, model refinement, dataset and tool development, portfolio construction support, and communicating results to technical and non-technical stakeholders.

Design, build, and deliver large-scale, always-on backend services and data-focused products. Work across cloud platforms, distributed systems, and machine learning pipelines. Participate in design reviews, mentor engineers, and provide technical leadership to improve system reliability, scale, and product impact.

The role involves designing and running machine learning systems for personalisation in fashion retail, collaborating with teams to improve algorithms and mentoring junior members.

Deliver and deploy ML and generative AI solutions across industries: design experiments, build production-scale models, identify business use cases, drive measurable value, consult with clients, and mentor team members.

The Principal Data Scientist will lead complex projects, drive innovation in AI solutions, mentor teams, and influence data science strategy.

Develop and own high-fidelity computational plasma models for semiconductor etching and deposition, validate simulations against process data, collaborate with Data Scientists/ML engineers, work onsite with customers to scope challenges, integrate simulation into AI workflows, lead projects and mentor juniors, and travel globally to deliver solutions.

The Senior Staff Machine Learning Engineer will develop and scale ML systems for content classification, moderation, and decision-making, ensuring quality and compliance across Spotify's platform.

Lead roadmap and end-to-end product delivery for assigned feature set: ideation, planning, build, launch, and growth. Drive customer validation, mentor junior PMs, collaborate with design and engineering, engage early adopters, and integrate AI/ML capabilities to inform decisions and enhance product value for banking customers.

Lead technical pre-sales engagements for Databricks, demoing Spark and data/AI solutions, building architectures, authoring reference materials, and collaborating with account teams to design and deliver customised proofs-of-concept and workshops.

Lead development and implementation of a global marketing AI strategy. Map and optimize marketing processes, architect AI-driven workflows, evaluate MarTech and agency AI capabilities, partner with IT/data teams, operationalize governance, and drive cross-functional adoption and change management to scale AI-enabled marketing globally.

Serve as a technical SME for the Geotab ecosystem: gather requirements, deliver demos and presentations, design tailored solutions, enable partners, support sales and product teams, document engagements, and drive partner upskilling and feedback to improve offerings.

Lead and coordinate cross-functional projects from planning through execution. Improve operational processes using data, budgets, KPIs and AI/automation tools. Create internal communications, manage multiple workstreams, drive stakeholder collaboration, and deliver measurable improvements in team efficiency and culture.

Lead product strategy connecting retail operations and accounting for Tekion's ARC platform. Own UK/Canada retail requirements, drive transformation-first customer engagements, define stock management and integration standards, collaborate across product, engineering and implementation, and represent Tekion externally to enable enterprise dealer adoption.

Lead development and implementation of the group's underwriting governance and execution framework. Provide oversight of underwriting strategy alignment, post-bind reviews, trend identification, and senior decision support using analytics and AI-enabled tools. Partner with underwriting, CUO, data, and technology teams to design strategies, produce executive materials, and drive governance improvements across the business.

Lead and grow the UK data organisation (Data Science, ML Engineering, Analytics Engineering, Data Engineering). Set strategy, priorities, and operating model; partner with product, commercial, clinical and ops stakeholders; drive international platform migrations (Databricks/Redshift to GCP), support new market launches, provide technical and architectural leadership, and build a high-performing team.

Lead deployments of AI-driven process control in heavy industry: integrate Gigaton AI into live plants, collaborate with operators and engineers, analyse plant data, design APC/MPC/PID-based control strategies, validate performance, and support scalable deployment playbooks while travelling to sites for commissioning and optimisation.

Build a greenfield ML lifecycle platform for financial crime detection: design declarative training pipelines, model packaging/serving, evaluation frameworks, monitoring and drift detection, and integrate with central ML infrastructure to improve data scientist productivity and ensure regulatory auditability.

Design, build, test, and deliver scalable machine-learning and NLP systems and large-scale data pipelines. Integrate ML models into production, write maintainable tested code, collaborate cross-functionally, and drive research-to-product development in an agile environment.

Develop, implement and optimise large-scale ML models for Graphcore hardware; benchmark and scale training/inference across thousands of accelerators; test internal releases, fix and review code; design and run experiments; collaborate with Research, Software and Product teams; engage with the AI community.

Design and build scalable AI-powered backend services and APIs in Golang for cloud-native, microservices-based platforms. Develop developer tools, ensure observability, CI/CD, and performance, solve distributed-systems challenges, and mentor engineering teams to deliver production-ready solutions.

Two-year graduate programme rotating across customer-facing operations to drive process improvement, automation, and data-driven decisions. You'll analyse problems, deliver projects, present results to stakeholders, and collaborate cross-functionally to improve customer experience and operational efficiency.

The FX Market Surveillance Product Director is responsible for the design and improvement of FX trade surveillance systems, ensuring compliance with regulations and market standards, collaborating with various teams to implement monitoring solutions, and defining key performance indicators for effectiveness.

The Research Scientist will conduct foundational machine learning research focusing on LLMs, collaborating with global teams, and engaging with academic communities to innovate AI systems.