Top AI Jobs in London

Review, rank, and improve AI-generated code to train LLMs: compare implementations, repair/refactor for correctness, efficiency, and style, and provide detailed feedback for RLHF pipelines. Work asynchronously as a remote contractor, injecting ratings, edits, and test results to improve model outputs.

Evaluate, rank, repair, and refactor AI-generated code to improve correctness, efficiency, and style; provide detailed written feedback for RLHF pipelines; and help maintain the code-evaluation and training workflow remotely.

Review, rank, repair, and refactor AI-generated code to improve correctness, performance, and style. Provide detailed written feedback and edits for RLHF pipelines, converting expert judgments into signals used to train models. Work asynchronously as a remote 1099 contractor.

Lead the development of AI-native features, collaborating with teams to create innovative solutions, while maintaining focus on user needs and market trends.

The Lead AI Creator will develop Kainos' AI narrative, produce diverse content rapidly, and collaborate to amplify brand presence while measuring effectiveness.

As a Senior AI Deployment Engineer, you'll develop and deploy AI software on cloud and edge devices, optimize AI models, and work with microservices and MLOps.

The Director will lead the assessment and piloting of emerging technologies, particularly AI, and drive their adoption across the organization while fostering a culture of innovation.

Lead technical discovery and implementation of AI/LLM-powered agents for enterprise procurement workflows. Design agent architectures, build and tune prompts, create integrations with ERPs/CLMs via middleware/iPaaS, drive deployments, enable customers, and feed product insights.

The Head of Research and Development for AI Safety will lead a research team focused on AI safety, drive the research agenda, manage publications, and influence AI safety strategies with industry impact.

Join Watershed's sustainability AI reporting team to prototype, build, and productionize AI features (LLMs, embeddings) for information extraction and report generation. Ship production-ready, well-tested full-stack code and keep systems current with state-of-the-art AI to deliver customer-facing product features.

The role involves managing the lifecycle of AI agent deployments, optimizing processes, ensuring performance through data analysis, and collaborating across teams to drive AI solutions.

Provide methodological and statistical leadership across projects, design and deliver advanced analytics and ML solutions (including deep learning and NLP), mentor staff, manage client relationships, and drive business development in health outcomes and pharmaco-economics.

Drive technical pre-sales for Databricks AI/BI product line: design engagement strategies, deliver demos/workshops, advise on lakehouse analytics, resolve tier-3 technical issues, and influence product roadmap to increase adoption and customer success.

Lead AI strategy engagements for clients: identify high-impact use cases, design AI roadmaps, estimate ROI, oversee implementation and transformation, manage cross-functional teams, and advise C-suite stakeholders.

Drive adoption of Thomson Reuters AI products among law students and early-career lawyers by building partnerships with law schools and training providers, running student engagement campaigns and training, integrating AI into curricula, capturing feedback for product teams, and owning KPIs for the education/early-career segment.

Design, build, deploy and iterate LLM-based applications and generative AI solutions. Partner with product and business teams to optimise internal workflows, implement cloud-based end-to-end solutions, and ensure reliability, scalability, and observability.

Design and build scalable microservices, APIs, and data pipelines for high-dimensional simulation data. Implement data storage and ingestion for ML workloads, enable BI and visualization tools, own features end-to-end, maintain CI/CD and observability, and collaborate with data scientists to ensure secure, reliable, performant systems.

Senior individual-contributor owning strategy and standards for conversational AI agents. Define agent reasoning, behaviour, safety, quality, measurement, and integrations; partner cross-functionally to translate business processes into scalable automation and guide architectural and operational decisions across tools, prompts, knowledge, and experimentation.

The Senior AI/ML Engineer at Nansen will develop AI models for blockchain data analysis, collaborating with teams to enhance platform capabilities and mentor junior engineers.

The Growth Marketing Manager will lead marketing initiatives, optimize the funnel, use AI tools for performance, and collaborate across teams to drive growth for Mindvalley’s Innovation Team.

As a Senior AI Research Scientist, you will lead AI research in LLM, MLLM, and computer vision, developing models and algorithms for real-world applications, while mentoring junior scientists and contributing to publications.

The AI Product Owner will define, shape, and deliver AI capabilities, manage the AI product roadmap, engage with clients, oversee SDLC delivery, ensure compliance, and support internal teams.

Design, build, and operate low-latency multi-agent LLM systems. Ensure high-quality real-time communication and optimize prompt programming and retrieval processes.

The Founding Marketer will drive campaigns, create AI-powered marketing infrastructure, craft compelling narratives, partner across teams, and experiment rapidly to generate inbound pipeline for Sequence's growth.

The AI Solutions Engineer will design and implement AI solutions, integrate ML models, mentor teams, and drive adoption of AI technologies across Multiverse's learning platform.