Top Machine Learning Jobs in London

Use life-science domain knowledge and data science to analyze Veeva and external datasets, build dashboards and pipelines, apply ML/NLP/GenAI, and present insights to senior pharma stakeholders to support R&D and commercial strategies.

Build and productionize large-scale ML and optimization systems for ads (ranking, targeting, campaign optimization, forecasting, measurement). Translate business problems into scientific solutions, partner with cross-functional teams, improve ad performance, lead technical design and experimentation, mentor junior scientists, and contribute to the applied science community.

Own the full sales cycle across EMEA (and MENA): build pipeline, close and launch deals, develop go-to-market strategy, expand regional footprint, cultivate long-term client relationships, represent Jampp at industry events (20%+ travel), collaborate cross-functionally, and lead local initiatives to grow mobile programmatic business.

Lead and develop a team of ML specialists to deliver production ML systems for fraud and financial crime. Set priorities, ensure model lifecycle practices (development, deployment, monitoring, governance), partner with Product, Risk, Engineering and Data, and raise standards for performance, explainability, reproducibility and observability while building an inclusive high-performing team.

Lead development and implementation of novel statistical methods and study designs for drug development. Provide statistical consulting, drive stakeholder engagement, oversee tools/software development, publish and present research, and mentor junior methodologists while collaborating across cross-functional teams.

Lead optimisation and configuration of the Pega Customer Decisioning Hub to embed customer contact strategy, enable personalised multi-channel marketing, and deploy advanced analytics and machine learning for next-best engagement. Support stakeholder enablement, upskill colleagues on Pega capability, ensure GDPR/PECR-compliant communications, and keep the platform aligned with industry best practices and Society goals.

Lead delivery of advanced analytics and data science for global clients, develop scalable AI-enabled analytics products (prediction engines, experimentation, MMM), embed analytics into client decision-making, and build capability across teams through playbooks and thought leadership.

Lead delivery of advanced analytics and AI solutions for global clients, design scalable analytics products, industrialise prototypes to production, embed measurement and experimentation, drive adoption across markets, and build analytics capability and thought leadership within the organisation.

Define and lead AI and data science strategy across ML, NLP, search, recommendation, experimentation, and generative AI. Lead and develop teams to deliver production-ready AI systems (LLMs, RAG, semantic search, embeddings), establish evaluation and responsible AI frameworks, and influence cross-functional stakeholders to align roadmaps and drive measurable product and business outcomes.

The Staff Machine Learning Scientist will design, develop, and maintain machine learning models for Depop's fashion resale platform, leading technical initiatives and collaborating across teams to drive innovation in ML solutions.

The role involves developing new AI model architectures and adapting existing models, conducting experiments, and contributing to technical strategy in a high-growth research environment.

As a Research Intern at Atla, you'll conduct machine learning research, contribute to product development, and output publications and datasets while collaborating with engineers on projects involving iterative model improvement and evaluation systems.

Seeking a Research Scientist to develop AI models for enhancing 3D reconstruction processes, requiring strong skills in computer vision and neural reconstructions.

The Enterprise Account Executive will manage the sales cycle, develop account strategies, engage with customers, and contribute to product growth.

Design end-to-end user experiences for cloud and infrastructure products, focusing on usability for developers and AI workflows while collaborating with engineering and product teams.

Manage and mentor Data Scientists in Payment Intelligence, oversee ML models for payment decisions, and guide strategic roadmaps while collaborating across teams.

The Reserve Engineer provides technical support for robotic hardware, resolves hardware failures, and assists with robot deployments while ensuring excellent customer service.

Lead engineering operations and team, ensure product alignment with strategy, drive project execution, and maintain regulatory compliance in healthcare technology development.

Work with sales, partners, product and industry specialists to design, demo and deliver Marketing Cloud solutions. Lead technical discovery and workshops, present ROI-focused demos, create reusable enablement assets, advise product teams, and support sales campaigns and events to grow pipeline and revenue.

Lead design and deliver scalable XVA risk software, embed AI/ML and Generative AI into workflows, own projects end-to-end, drive architecture and Agile delivery, ensure regulatory compliance, and mentor engineering teams.

Lead Professional Services business development and strategic advisory for Workday platform deployments. Position AI, Extend, and Prism Analytics to drive transformation, align with Global SIs, run consultative discovery, negotiate services agreements, forecast pipeline, and build executive relationships to deliver value-based outcomes.

Own and accelerate an enterprise pipeline for Global 2000 customers, lead complex multi-stakeholder sales cycles, position Algolia's AI-first search solutions, develop account/territory strategies, expand accounts, partner with Solutions Engineering for demos/POVs, and forecast using MEDDPICC.

The Senior Program Manager will lead R&D portfolio management, ensuring clarity and effective execution of research programmes while collaborating with senior leadership.

The Staff Data Scientist will provide technical leadership in Claims, developing ML and AI systems for risk decisioning and fraud detection, collaborating with cross-functional teams to scale decisioning and enhance claims automation.

Dragonfly is seeking Software Engineers for various portfolio companies, focusing on crypto technologies. Engineers of all experience levels are needed across multiple stacks.