Top AI Jobs in London

As a Full Stack Engineer at Miro, you will develop AI-powered features, collaborate with teams, and mentor other engineers to enhance user experiences.

Design and implement AI-powered internal tools for GTM use cases, managing full lifecycle from data modeling to production. Collaborate closely with GTM teams to translate data into actionable insights with a focus on measurable business impact.

The Investment Solutions AI Product Manager leads product management for the e-connectivity team, ensuring alignment with business needs and delivering AI-driven solutions. Responsibilities include stakeholder coordination, roadmap prioritization, and overseeing development quality.

Lead the strategy and rollout of AI products within a transformation programme, ensuring adoption and collaboration among stakeholders, while maximizing impact and aligning organizational goals.

Lead the design and delivery of GenAI solutions, leveraging LLMs and RAG architectures while integrating with enterprise systems. Focus on production-grade implementations and collaboration across teams for digital transformation efforts.

The Client Engagement Manager will oversee platform implementations, build client relationships, provide training, document processes, and collaborate with teams to enhance customer experience.

Manage trading workflows and risk monitoring using AI. Develop models for predictive risk and automate manual processes to enhance P&L analysis.

As AI Mobilisation Lead, drive AI integration into operational resilience. Assess AI risks and ensure alignment with regulatory standards across teams.

As a Senior Solution Architect, you'll develop client relationships, lead technical sessions, translate requirements into solution architectures, and represent Mirantis at events while showcasing the AI Infrastructure platform.

The AI Business Development Specialist will identify business opportunities, build client relationships, and promote AI solutions in various sectors, with a focus on the MENA region.

The AI Software Engineer will train large-language models, compare code snippets, and provide feedback to improve AI-generated code. Requires strong C++ skills and attention to detail.

Help train large-language models to write production-grade code by ranking, repairing, and providing feedback on AI-generated code snippets, with a focus on logical correctness and performance.

Help train large-language models to write production-grade code by comparing, ranking, repairing, and refactoring AI-generated code, while providing feedback for reinforcement learning.

As an AI Software Engineer, you'll help train large-language models in Rust by comparing code snippets, repairing AI-generated code, and providing feedback to enhance model learning.

This role involves training large language models to improve code through evaluation and feedback, focusing on correctness, efficiency, and communication.

Join our team to help train large-language models by evaluating and improving AI-generated code, leveraging your coding and communication skills.

The role involves training large-language models by evaluating and refining code snippets, providing feedback, and maintaining an RLHF pipeline. Candidates need strong Python skills and code review expertise.

As Legal Counsel - Privacy, Product & AI, you will advise teams on data protection and AI compliance, draft contracts, and implement legal tools.

The Head of AI Assurance will develop AI safety frameworks within financial services, generate new business, and enhance market profile through thought leadership and senior stakeholder engagement.

As a Responsible AI & Adoption Consultant, you'll drive Responsible AI adoption, shape impactful strategies, engage with policymakers, and advise clients on ethics, governance, and human-centric design. You'll manage a team and foster innovation within AI practices.

Join the Data Science team at MAGIC AI to enhance ReflectAI® tech. Collaborate on pose estimation, develop algorithms, and optimize AI models for real-time feedback, ensuring effective communication with cross-functional teams.

The AI Engineer will develop AI-driven features, utilizing LLMs and agent architectures, ensuring quality and customer impact through collaboration in a dynamic team.

As an Applied AI Engineer, you'll manage ML model lifecycles, build data pipelines, develop AI features, and collaborate with backend engineers to integrate models into production systems.

As an AI Deployment Architect, you will configure, deploy, and troubleshoot AI agents, working directly with clients to ensure their needs are met through customized solutions and continuous feedback loops.

The Senior Product Owner (Data / AI) will be responsible for leading the development of data-driven product domains, collaborating with analytics and AI teams, defining product strategies, and ensuring the execution and delivery of data & AI product features.