Top Machine Learning Jobs in London

Design and validate threat models for agentic AI systems, create adversarial experiments and synthetic environments, develop static and dynamic risk analysis, fine-tune and evaluate models, and build production-ready guardrails, monitoring, dashboards, and evaluation infrastructure. Optimize security systems for latency, cost, reliability, and measurable real-world performance while translating research into product capabilities.

Lead the technical strategy, design, and production integration of fault detection and fallback systems for autonomous vehicles. Develop robust robotics solutions, collaborate with machine learning and software teams, guide architecture decisions, and improve overall system safety and reliability. The role also involves mentoring, defining acceptance criteria, analyzing fleet data, and potentially building monitoring, debugging, and real-time systems for large-scale driverless vehicle operations.

Develop and improve InstaLILY’s core AI platform, collaborating with product, design, UI/UX, and business teams to deliver reliable customer-focused features. The role includes writing software, testing, supporting CI/CD practices, maintaining technical quality, and staying current with AI and software engineering technologies. Candidates should have 0–2 years of software engineering experience, programming experience in Python and JavaScript, and familiarity with cloud computing or AWS, Azure, or GCP.

Build and deploy LLM-powered workflows for bioinformatics and metabolomic chemistry. Translate scientific questions into reliable AI tasks, query biological data and knowledge graphs, generate traceable recommendations, and develop benchmarking and evaluation infrastructure. Collaborate with wet-lab scientists, chemists, microbiologists, and engineers while contributing Python code, data architecture, pipelines, and model deployment to a shared production codebase.

Mercor is offering $5 million in grants for independent researchers, academics, PhD students, and small teams conducting frontier AI safety research. Focus areas include misalignment, sandbox escape, evaluation awareness, interpretability, oversight and control, and red-teaming. Funding may support researcher time, API credits, and conference attendance. Applicants should submit a focused expression of interest describing their team, background, research proposal, outputs, impact, timelines, and resource needs.

Leads measurement strategy across PlayStation by designing experiments, causal inference methodologies, statistical models, and machine learning solutions. Establishes experimentation best practices, influences platform capabilities, partners with product and business leaders, communicates analytical recommendations, and mentors data scientists and analysts. The role provides technical leadership for evidence-based product and commercial decisions affecting millions of players.

Develop and evolve Ki’s end-to-end MLOps platform, including feature stores, model registries, monitoring, governance, and lifecycle management. Enable safe production deployment of machine learning, actuarial, and rules-based models. Own roadmap development, cost and vendor decisions, regulatory alignment, stakeholder adoption, and knowledge sharing. Coach early-career engineers and drive operational improvements across the digital underwriting capability.

Design, build, and optimize scalable software platforms supporting quantitative research and financial trading. Responsibilities include developing trading systems, modeling and simulation frameworks, research tools, machine-learning infrastructure, and high-performance distributed systems. The role involves collaborating with quantitative researchers, owning solutions end to end, applying strong software fundamentals, improving scalability and performance, and evaluating emerging technologies.

Provides Tier 2 workplace technology support across Windows and macOS environments. Responsibilities include incident and service request resolution, ticket management, asset lifecycle administration, employee onboarding and offboarding, AV/VC support, technical troubleshooting, documentation, security compliance, and collaboration with Tier 3 teams. The role is onsite in London and supports internal employees through a Tech Bar, ITSM platform, remote tools, and internal events.

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.

Lead and mentor an agile team to design, develop, secure, and operate scalable cloud-native applications using modern front-end tech and AI-assisted engineering practices; drive automation, code quality, resiliency, and operational stability.

Lead regional field sales teams, develop sales strategies and account plans, manage pipeline and forecasts, recruit and coach sales managers, close enterprise technology deals, and grow business through customers, resellers, and partners. The role requires strong technical knowledge of cybersecurity, cloud, networking, and IT infrastructure solutions, executive-level selling skills, and the ability to manage remote teams across the NEMEA region.

Design, develop, and deploy software solutions for automated trading systems while collaborating with researchers on technology priorities.

Lead TIDAL's product and brand design vision, drive complex end-to-end design initiatives, define systems and standards, pioneer AI-driven design, partner with Product/Engineering/ML, mentor designers, and identify new business opportunities to elevate artist-focused products.

AI/ML Engineers will build and deploy AI-native products, autonomous agents, LLM applications, RAG systems, and production ML pipelines. Responsibilities may include integrating AI into crypto infrastructure and consumer products, fine-tuning and evaluating models, optimizing inference, and developing agentic workflows and machine-to-machine payment systems. Engineers will work end-to-end with high-ownership teams in fast-moving environments.

Drive adoption of Rapsodo Golf solutions across UK golf ranges, clubs, and facilities. Responsibilities include prospecting, relationship building, on-site demonstrations, full-cycle sales, contract negotiation, installation coordination, post-installation support, CRM pipeline management, territory planning, event representation, and sharing customer and competitor insights with internal teams.

Lead the founding London enterprise sales team by recruiting and coaching account executives, managing complex AI infrastructure deals, shaping European go-to-market strategy, and acting as a player-coach. Partner with Marketing, Product, Engineering, and Legal on enterprise requirements, technical evaluations, procurement, and roadmap input. Build consultative selling practices and a culture of accountability while carrying deals during the team’s early growth.

Own strategic AI-native accounts from initial sale through expansion. Lead complex technical evaluations and multi-stakeholder sales cycles, build relationships with founders and engineering leaders, coordinate applied research and infrastructure teams, and influence product roadmap decisions. The role requires selling SaaS or infrastructure solutions, understanding open-source models and AI infrastructure, managing technical projects, and aligning cross-functional teams in a fast-growing environment.

Own and build Baseten’s EMEA sales organization from the ground up, initially serving as a player-coach in London. Responsibilities include managing the region, hiring and onboarding 20+ employees, developing pipeline, closing enterprise deals with technical buyers, localizing the go-to-market motion, establishing the company’s regional presence, and partnering with US-based Sales, Marketing, Revenue Operations, Solutions, and Recruiting teams. The leader will also set standards for execution, forecasting, and organizational growth.

Build qualified sales pipeline by prospecting target accounts through email, calls, and LinkedIn; qualify inbound leads; personalize outreach; educate prospects about AI inference solutions; meet pipeline targets; collaborate with Sales and Marketing; and stay informed on AI/ML trends.

Deliver hands-on GenAI implementations for international government customers, from identifying mission needs through architecture, prototyping, evaluation, production readiness, adoption, and handoff. Partner with agencies, technical teams, systems integrators, cloud providers, and senior stakeholders while addressing privacy, data residency, security, identity, procurement, and regulated-environment requirements. Build applications with OpenAI technologies, contribute developer resources, share best practices, provide product feedback, and manage multiple concurrent customer engagements.

Own strategic AI-native and enterprise accounts across the full sales cycle, from pipeline generation and prospecting through closing and expansion. Partner with Solutions, Engineering, and Research teams to design technical solutions and proof-of-concept evaluations for inference and post-training workloads. Build executive and technical relationships, manage complex sales cycles, identify customer use cases, provide product feedback, and improve sales processes. The role requires strong B2B technology sales experience, technical fluency, and a record of closing complex strategic deals.

Build and improve production AI systems, including chatbots, autonomous account actions, document extraction pipelines, and LLM-driven case-management workflows. The role covers discovery, prototyping, deployment, evaluation, monitoring, prompt design, retrieval, agent workflows, and identifying manual processes suitable for automation.

Lead design and delivery of high-performance, real-time data pipelines and analytics for trading. Drive AI-enabled data engineering, mentor engineers, manage global initiatives, and improve SDLC, testing, and operational reliability.

Senior front-end engineer on an agile Equities Sales & Trading team delivering secure, scalable cloud-native applications. Provides technical leadership, writes and reviews production code, drives design decisions, optimizes UI performance for high-frequency data, and advocates firmwide engineering practices and tools.