Top AI Jobs in London

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.

Build and operate distributed backend services and genomic reasoning engines that combine whole genome bioinformatics with AI. Design scalable data models, retrieval and vector search systems, and deterministic guardrails to ensure scientifically accurate, explainable genomic AI for production use.

Design and build production AI systems and distributed backend services that enable genomic reasoning, retrieval, and data platforms. Integrate genomic annotations and interpretation logic, architect high-performance data models and storage across PostgreSQL, DuckDB, Qdrant, Redis, and Spark. Ensure AI outputs are accurate, explainable, and grounded in genomic evidence while collaborating across engineering and bioinformatics teams.

Lead architecture and delivery for Fortives HR technology ecosystem, owning Oracle HCM, Boomi integrations, ServiceNow HRSD, Eightfold and LMS platforms. Define API-first integration patterns, implement AI/automation use cases, ensure data governance and compliance, and guide integration engineers while partnering with HR and IT stakeholders to modernize HR systems.

Ship real open-source integrations and MCP servers to bring SearchApi to agent and automation frameworks. Create PRs, example apps, docs, and integration guides. Stay current with the agent ecosystem, pick high-leverage targets, and work independently to deliver production-ready integrations.

The Senior AI Transformation Consultant works with clients to identify AI opportunities, define robust business cases, and oversee AI project deployments, ensuring solutions deliver value.

Lead and build Maze’s new AI-native Market Research service: define research vision and methodologies, recruit and manage a research team, own delivery quality, partner with Product/Engineering and GTM, and serve as executive research lead on strategic customer engagements.

The role requires deploying AI solutions and automations for clients, building prototypes, integrating systems, and collaborating with various teams while ensuring effective client interaction.

As a Technical Lead, you will guide software engineering teams, translate client requirements into applications, ensure best practices, and shape technical direction while mentoring team members.

Create high-quality video content and integrate AI tools into production workflows, combining storytelling and video craft to enhance cinematic quality.

Design, scale, and productionize ML and physics-based scientific code for drug and materials discovery. Transition prototypes to robust products, orchestrate distributed GPU training, implement hardware optimizations, and support model lifecycle and integration into large-scale simulation frameworks.

Architect and build agentic workflows combining LLMs, reasoning, and data pipelines. Lead ML/NLP product development from training to deployment, drive experimentation, integrate intelligent agents into recruiting workflows, mentor engineers, and improve reliability, personalization, and observability.

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.

Lead cross-functional engineering teams to design, deliver, and evolve cloud-native, event-driven insurance applications. Own architecture, roadmap, and delivery for policy, claims, underwriting, and compliance systems while ensuring regulatory adherence, vendor management, Agile/DevSecOps practices, and engineering KPIs.

The role involves designing, implementing, and delivering AI/ML solutions, developing machine learning models for scientific tasks, and collaborating with experts for data processes.

The Director of Business Development will drive revenue through creating strategies for new business, managing client relationships, and overseeing sales processes while ensuring high service standards.

The AI Enablement Intern at Providence will support AI solutions for investment teams, build workflows, drive adoption, and improve decision-making across portfolio companies.

The role involves applying diffusion techniques and developing AI models to enhance 3D reconstruction pipelines for various industries.

Join Abound's one-year Graduate Scheme on the AI Engineering route to build production-grade Generative AI and agent solutions. Work cross-functionally to design prompts, integrate LLMs with tools, APIs and databases, write scalable Python code, and evaluate AI systems. You'll ship code from week one, receive mentorship, and may convert to a permanent role based on performance.

The AI Enablement Engineer leads programs for engineering teams to integrate AI, teaches best practices, and develops scalable learning models.

Drive research and engineering for large-scale LLM and multi-modal pre-training: design architectures, curate massive datasets, run distributed training on multi-node GPU clusters, optimize model efficiency and alignment, debug long training runs, and scale distributed training systems to improve cross-modal performance.

The AI Research Engineer will research and develop novel model architectures, adapt open-source models, and contribute to the technical strategy and culture of the team.