Top AI Jobs in London

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.

Join Tether as an AI Research Engineer focusing on model compression and quantization for AI systems. You'll innovate in reducing model footprint for multimodal architectures while applying advanced compression techniques, ensuring high performance on edge devices.

As an AI Research Engineer, you will develop multi-modal reinforcement learning systems, focusing on optimization across data modalities, conducting research on algorithms, and building infrastructure for scalable training and evaluation.

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.

Lead design and delivery of production-grade AI systems and Digital Workers. Embed with enterprise clients to translate workflows into scalable agentic architectures combining LLMs, RAG, multi-agent orchestration, retrieval, and cloud integration. Own end-to-end technical delivery, guide engineering teams, set technical direction, and ensure reliability and performance in production.

Build and deploy production-grade autonomous AI systems (Digital Workers) for enterprises. Embed with clients to map workflows, integrate models, data, and infrastructure, and deliver scalable agentic solutions using LLMs, RAG, multi-agent coordination, orchestration, and cloud platforms.

Develop computer vision models for object recognition and video understanding while evaluating and improving their performance for real-world applications.

Nebius seeks a Senior ML Engineer for AI R&D focusing on applied research in reinforcement learning and agent training, requiring deep expertise in machine learning and software engineering.

The AI Developer will design, implement, and deploy AI agents and workflows, integrating advanced models and ensuring reliable performance in production environments.

Build and deploy production-ready AI/ML systems across the full lifecycle, including agentic systems (RAG, prompt engineering), non-GenAI models (recommenders, forecasting), APIs/microservices, CI/CD and IaC, monitoring and guardrails, and cross-functional collaboration to ensure scalable, secure, and observable ML solutions.

Lead design and delivery of production LLM-powered agent systems and firm-wide agent standards. Build reference agent apps, connect agents to internal data/APIs, establish security and governance for AI, adopt deployment and observability infrastructure, and partner with stakeholders to identify high-value use cases.

Lead AI-focused presales pursuits for ERP/EAM/FSM, translate AI capabilities into domain-specific solutions, create demos and proof-of-value, mentor presales, shape GTM strategy, and collaborate cross-functionally to drive technical wins and portfolio adoption.

The Commercial Associate will engage in outbound sales strategies, account prioritization, and collaborate with Account Executives to drive opportunities, aiming for fast growth and skill development in a technical B2B environment.

Lead architecture and delivery of enterprise-scale data and AI projects on Google Cloud. Provide pre- and post-sales technical advice, design and migrate cloud solutions, mentor architects, collaborate with partners and sales, define best practices, and build next-generation ML products and scalable production-grade platforms.

Design, build and maintain modular, scalable, performant backend systems across the full software lifecycle; diagnose and resolve system issues; mentor junior engineers; collaborate with product and cross-functional teams; iterate quickly to deliver customer-focused features.

Freelance AI Engineer to design, develop, and deploy AI and machine learning solutions. Responsibilities include algorithm development, data analysis, building production-ready models, and contributing to the platform's AI initiatives in a fully remote capacity.

Build and scale AI-driven automation solutions using LLMs and agent frameworks. Design multi-step workflows, integrate AI with internal systems (HR, finance, legal, ticketing), automate document processing and data extraction, and train internal teams. Collaborate with technical leads, product, and IT to deliver practical, production-ready automation and iterate quickly.

Mentor apprentices on an AI Champion programme by assessing progress, supporting portfolio development and EPA preparation, providing technical advice and regular feedback, contributing to curriculum content, safeguarding learners, and liaising with employers and the Delivery Team to drive AI adoption.

Mentor apprenticeship learners to identify and implement AI-driven workflow improvements, assess progress against the apprenticeship standard, support portfolio and EPA preparation, provide technical support and mentoring sessions, report learner progress, and uphold safeguarding and equality responsibilities.

Work as a quantitative consultant delivering insight programmes that combine advanced analytics, mixed methods and AI to solve client problems. Contribute to analysis, synthesize evidence, build consultancy skills, explore AI tools, support business growth and help shape proposals and client-facing work.

Design, build, and deploy production-ready AI algorithms and high-scale evaluation pipelines focused on LLMs and patent generation. Implement advanced prompt engineering, translate research into product across the stack (Python, Postgres, React/TypeScript), and benchmark models to drive R&D decisions.

Design, build, and ship production LLM-based systems and agentic workflows. Develop core learning libraries, human-in-the-loop feedback loops, confidence scoring, and scalable agent orchestration. Work with enterprise customers to prototype, deploy, and generalize solutions back into the platform.

Embedded recruiter deployed inside a frontier AI lab to drive Sales hiring. Operate as an extension of client and employer brand, source and hire top-tier sales talent, build hiring foundations, and manage hiring processes with data-driven communication and high ownership.

Embed with a frontier AI lab to source and hire world-class sales talent for SaaS/AI/deep-tech roles. Act as an extension of the client brand, build hiring foundations, operate with data-driven communication, bring order to ambiguity, and apply high agency and emotional intelligence to drive mission-critical hiring.