Top Machine Learning Jobs in London

Lead ML Engineer to design and build MCP servers, Skills, and agentic orchestration for an enterprise agent platform. Implement APIs, secure wrappers, RAG and prompt-based flows, deploy on containerised/Kubernetes platforms, and shape developer patterns, governance, and operational readiness while partnering with product teams, SRE and QA.

Lead global pricing strategy and modernization for wholesale and specialty insurance, driving analytics, AI/ML integration, pricing model governance, catastrophe and transaction-level pricing support, and talent development to improve underwriting performance and return on capital.

Lead advanced statistical and machine learning analyses to generate actionable business insights; partner with cross-functional teams to design data-driven solutions; manage large datasets with strong governance; develop and maintain predictive models to forecast trends; communicate findings to stakeholders and stay current on industry technologies.

Serve as the technical AI/ML lead in customer engagements: translate customer needs into robust solution designs, build stakeholder relationships, contribute to proposals and product roadmaps, prototype approaches, and ensure delivered ML systems are operationally valuable.

Build and maintain production Golang backend services and data pipelines for an AI-driven investment platform. Design APIs, improve performance, reliability, and observability, debug production issues, and collaborate with AI and product teams to ship scalable, low-latency systems.

Owns release gates and quality standards across Wayve’s machine learning training and delivery lifecycle. Reviews model and metric changes, validates evaluation results, identifies pipeline bottlenecks, and builds checks and automation with AI Platform and CI/CD teams. The role also improves evaluation methodology, model delivery workflows, and MLOps practices while ensuring model releases meet safety and performance standards.

Develop efficient generative world models and planners for closed-loop autonomous-driving simulation. Responsibilities include designing diffusion or transformer-based models, enabling interactive agent simulation, optimizing inference latency and compute efficiency, defining evaluation metrics, integrating models into training and evaluation workflows, measuring sim-to-real performance, mentoring researchers, and contributing to technical roadmaps and publications.

As a Senior Product Engineer, you will develop backend and frontend systems, mentor engineers, and enhance product architecture at Intercom.

Drive innovation in post-training methodologies for AI models, focusing on agentic behaviors, tool use, and enhancing model capabilities for real-world applications.

As an AI Research Engineer, you'll optimize model deployment and inference architectures for AI systems, enhancing performance across various applications, especially on resource-constrained devices. Responsibilities include designing efficient serving architectures, conducting inference tests, and collaborating with teams to integrate solutions.

As an AI Research Engineer, you will develop and optimize vision-language models, managing the full model lifecycle from training to deployment, focusing on efficiency and innovation in multimodal architectures.

The algorithm engineer will develop machine learning products for underwriting risk assessment, ensure algorithm availability, and guide junior team members.

As a Software Engineer at Prodia, you will optimize image/video models, build APIs, and improve distributed job scheduling, focusing on fast and reliable performance.

Lead and architect an area of the enterprise product, write production code, mentor and manage engineers, conduct code reviews, own technical decisions, collaborate with PMs/designers, promote security best practices, and contribute to roadmap and stakeholder communication.

Lead and grow a TPM function for the Data org, owning delivery of data platform, ingestion, pipelines, enrichment, labeling, and dataset quality. Drive flagship programs, establish scalable governance and KPIs, coordinate cross-functional dependencies, and partner with engineering to improve data quality, throughput, cost, and time-to-insight.

As a Research Engineer, you'll improve RL training infrastructure, identify bottlenecks, collaborate with teams, and enhance reliability of research runs.

Isomorphic Labs seeks to recruit interested candidates for roles in software engineering, machine learning research, computational chemistry, and project management for future openings.

The role involves building and implementing machine learning models, collaborating with cross-functional teams to solve complex problems in data science.

The Executive Director leads HEOR Consulting projects, manages teams, ensures client satisfaction, and drives AI integration within healthcare solutions while overseeing business development and strategic planning.

The EMEA Events Marketing Manager will develop and execute strategic event marketing programmes while overseeing multiple projects, ensuring high-quality attendee experiences, and collaborating with cross-functional teams.

Lead and scale Mimica's product organisation, define global product strategy and roadmap for AI-driven task/process mining and automation, mentor product and design teams, improve product operations and discovery, align cross-functional stakeholders, handle escalations, and hire and forecast team needs.

As a Senior Impact Analyst, you will analyze sustainability challenges, design and manage interventions, and work closely with smallholder communities, emphasizing rigorous research and collaboration.

Embed with engineering clients to own full-cycle technical hiring for software, AI/ML, infrastructure and data roles. Run deep intakes, headhunt passive candidates, coach hiring managers on interview design and calibration, build hiring foundations, report on pipeline health, and use/builder recruitment AI agents to scale impact.

Design and build models, strategies, and systems to price and trade financial instruments. Work with researchers, engineers, and traders on dataset generation, time-series analysis, feature engineering, model building, hyperparameter tuning, and distributed/deep-learning training at large scale.

Work with full-time researchers to identify market signals, analyze large datasets, design experiments, generate datasets, perform time-series analysis, engineer features, build and test models, and help create and productionize trading strategies. Participate in classes, seminars, and collaborative learning activities.