Top Machine Learning Jobs in London

Lead strategy and delivery of agentic AI across the Commercial & Investment Bank: design, build, and productionize multi-agent systems and RAG pipelines; integrate tools and cloud deployments; implement evaluation, safety, and observability; partner with stakeholders to deliver business impact; and mentor teams on LLMs, agent frameworks, and best practices.

Lead design and delivery of applied AI/ML solutions for data management and governance. Build prototypes, collaborate with business and engineering teams, document models and experiments, present results to stakeholders, and adopt emerging LLM/ML techniques to drive transformation.

Lead applied AI/ML efforts to design, build, deploy, and maintain production ML services (NLP/CV focus). Collaborate with engineering, cloud, and SRE teams, research models, ensure MLOps best practices, and document processes for regulatory compliance.

Lead design and delivery of production-grade AI/ML and agentic solutions for the LLM Suite platform. Own architecture, implementation, and operational stability using public cloud services and agentic frameworks. Build GenAI services, integrate LLMs, ensure secure high-quality code, and improve platform scalability and reliability through collaboration and communities of practice.

Design, build, and operate LLM inference backend services focused on routing, batching, scheduling, streaming, and quota management. Implement APIs/SDKs, profile and optimize performance (CPU, memory, network, GPU), improve reliability and observability, support CI/CD-safe deployments, and learn LLM serving fundamentals while applying responsible AI and enterprise-authorized AI-assisted development tools.

Lead research and engineering of state-of-the-art ML solutions (NLP, LLMs, recommendation systems). Drive experimentation, design training frameworks, build scalable production deployments, collaborate with cross-functional teams, publish research, and develop firm-wide ML frameworks while adhering to compliance requirements.

Lead design and delivery of production-grade AI/ML solutions for Market Operations. Manage and mentor a team of data scientists, partner with AI engineering and stakeholders, ensure robust MLOps, model governance, deployment, monitoring, and documentation while driving measurable operational impact.

Lead a small team of AI specialists to build horizontal capabilities (APIs, libraries, services) for document/email/speech domains, collaborate with Line of Business AI teams to solve priority use cases, design and maintain production model training/serving pipelines, mentor engineers, and drive best practices and thought leadership in applied AI.

Lead end-to-end delivery of applied AI/ML solutions for consumer banking. Partner with business and engineering to design, deploy, monitor, and govern production LLM/GenAI systems. Build and coach cross-functional teams, create reusable architectures and playbooks, ensure compliance, and present results to senior stakeholders.

Support design and rollout of AI/ML and Generative AI governance across CIB: build executive reporting and dashboards, update governance documentation, deliver training and communications, monitor compliance, remediate issues, and partner with data science, engineering and business stakeholders to implement governance tooling and process improvements.

Leads AI engineering for Media UK&I by identifying high-value opportunities, translating business problems into scalable solutions, guiding prototyping through production, and building an AI engineering team. Establishes engineering standards, integrates solutions with enterprise platforms, and embeds responsible AI governance, testing, monitoring, security, privacy, and human oversight. Partners with media, product, data, technology, and operational teams to drive adoption and measurable business value.

Build and improve ranking, personalization, recommendation, and notification-targeting models that drive adoption of grocery, retail, and other new marketplace verticals. The role involves productionizing end-to-end machine learning systems in Python, optimizing homepage and landing-page experiences, and translating user behavior into relevant recommendations. Candidates should have at least three years of ML engineering or data science experience and backgrounds in personalization, ranking, or recommender systems.

Lead the AI Engineering capability for dentsu Media UK&I by identifying, designing, building, governing, and scaling practical AI solutions across media workflows. The role manages and coaches AI engineering teams, translates business needs into solutions, establishes engineering standards, integrates platforms and data, and embeds responsible AI controls including testing, monitoring, security, privacy, and human oversight.

Investigate and resolve complex credit card fraud, consumer disputes, Section 75 claims, and chargebacks in compliance with Mastercard guidelines. Communicate empathetically with customers during challenging fraud scenarios, identify emerging trends and inefficiencies, support process improvements and automation, and stay current with fraud typologies and regulatory changes. The role requires strong organization, judgment, confidentiality, communication, and customer-protection skills.

Deliver advanced analytics, dashboards, and predictive insights using BI and AI to support decision-making. Establish data governance, design data lakes/marts, standardise visualisation, enable federated self-service, and improve data quality and reporting across the bank.

Develop machine learning systems for Deliveroo's marketplace, focusing on projects like rider pricing and delivery time predictions. Collaborate with cross-functional teams, design ML models, and ensure effective productionization of solutions.

As a Senior Machine Learning Engineer, you will design and productionize ML systems, collaborate with cross-functional teams, and mentor junior engineers to solve complex business challenges at scale.

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.

Validate and benchmark ML models on Graphcore's software/hardware stack. Create automated benchmarking pipelines, run open-source models, design targeted tests for numerical precision, quantisation, attention, distributed execution, and debug performance and correctness issues across frameworks and environments.

Design and build test infrastructure, automation, and tooling to validate ML software stacks and hardware; shape test architecture across CI pipelines, frameworks, simulators, emulators, and large ML workloads; mentor engineers and own complex validation projects.

Validate and benchmark ML models and stacks on Graphcore hardware. Build automated benchmarking pipelines, run open-source models, create targeted tests for numerical precision, quantisation, distributed execution and subgraphs, and debug performance and correctness across frameworks and execution environments.

As Lead Data Scientist, oversee project teams delivering AI solutions, mentor junior team members, and shape technical strategy for financial services clients.

As a Machine Learning Engineer, you will develop software solutions using machine learning, collaborate with clients, and deliver impactful projects working within cross-functional teams.

As the Technical Director of AI Safety, you'll lead AI safety initiatives, oversee R&D, mentor teams, and drive innovations, representing Faculty in global AI safety discussions.

Design and ship machine learning models for optimizing messaging on multiple channels, focusing on long-term user outcomes and experimentation.