Artificial Intelligence Jobs

eFinancialCareers · London · £110,000 – £140,000 pa

You will join a small AI labs team as one of two senior engineers, building Agentic AI solutions for internal investment, sales and marketing departments, taking projects from inception to production in roughly three-month cycles. Work centres on Python, AWS, LangChain and LangGraph, with client demos and potential partnerships, before handing solutions to departmental tech teams.

Anthropic · London · £260,000 – £630,000 pa

Blends research and engineering to advance reinforcement learning for large language models, building agentic capabilities like computer use and autonomous code generation. Involves architecting distributed RL training infrastructure across GPU clusters, designing novel training environments and evaluations, and profiling and optimizing the stack. Works closely with alignment, red team, and production training groups.

Anthropic · London · £260,000 – £630,000 pa

Own critical parts of a production pretraining pipeline, covering performance optimization, observability, reliability and hardware debugging across the full training stack. The role sits at the boundary between research and engineering, with on-call incident response during model launches and close collaboration with teams in SF and London. It is unusually operational for a research engineering position, offering hands-on work with some of the largest training runs in the industry.

Databricks · London

Customer-facing pre-sales architect driving adoption of Databricks' AI product line across a local EMEA territory, paired with an Account Executive to design and execute engagement strategies. Leads design and implementation of production agentic AI use cases using Agent Framework, AgentBricks, MLflow evaluation and tracing, while acting as tier-3 escalation for complex field challenges.

Entrust · London

Builds and operates production ML systems for document classification and extraction, using LLMs/VLMs and traditional ML to process government identity documents at scale. Owns features from RFC through deployment, optimising GPU inference and training/evaluation pipelines, and mentors engineers within a squad-based team.

University of Surrey · Guildford · £21,805 pa

Develops next-generation federated machine unlearning algorithms that deliver verifiable, robust erasure without harming model performance or participant privacy. Research spans certified unlearning with formal guarantees, robustness to adversarial relearning, federated-specific benchmarks, and scalable unlearning for foundation models, supervised by Dr Pedro Porto Buarque de Gusmao and Dr Frank Guerin.

Entrust · Lisbon, Portugal

Builds and operates production ML systems for document classification and extraction, using VLM/LLMs and traditional ML to power identity verification for millions of users. Leads technical design from RFC to deployment, optimises GPU inference, and designs training, evaluation and labelling pipelines. Works in a squad-based team alongside Applied Science, Product and Data Science, mentoring engineers and driving reliability and scalability.

NVIDIA · United Kingdom

Builds production-quality C++ components, APIs and integrations for NVIDIA's AI-powered developer-tools ecosystem, connecting native C++ tools to the Genie knowledge service via Python, MCP and REST APIs. Also contributes to agentic workflows, retrieval and ingestion pipelines, evaluation infrastructure and enterprise integrations, mentoring engineers and driving initiatives from exploration to deployment.

NVIDIA · Switzerland

Builds production-quality C++ components, APIs and integrations for NVIDIA's AI-powered developer-tools ecosystem, connecting native C++ tools to retrieval and agentic services via Python, MCP and REST. Involves systems architecture, concurrency, performance optimisation, mentoring and driving initiatives from exploration to production.

Isomorphic Labs · Lausanne, Switzerland

Architect and secure an AI-first drug discovery platform, reporting to the CISO. You will build AI-specific risk frameworks, protect model artifacts, deploy LLM and agentic guardrails, and lead AI security incident response across distributed training and inference infrastructure.

AI Security Institute · London

Senior individual contributor building and owning shared platform, tooling and infrastructure for a research team, including LLM-based agent systems, evaluation frameworks and supporting infrastructure. Works closely with interdisciplinary researchers to translate varied needs into maintainable Python systems, with strong engineering discipline around testing, documentation and observability. Also contributes to architectural decisions, engineering standards and mentoring through code review and knowledge sharing.

Faculty · London

Lead the technical strategy, architecture and deployment of secure AI systems across high-stakes domains, bridging research and production impact. The role involves capability testing for Frontier AI models, multi-agent systems, scalable cloud infrastructure and safety-first frameworks, while advising senior clients and mentoring engineering talent.

Faculty · London

Drives technical strategy, architecture and deployment of secure AI systems across high-stakes domains, bridging AI research and production. Leads capability testing for Frontier AI models, builds scalable ML infrastructure and multi-agent tooling, and advises senior client stakeholders while mentoring engineers.

83zero · London · £65,000 – £80,000 pa

Builds GenAI proof-of-concepts and production systems for clients, using RAG, intelligent agents and LLM frameworks alongside full stack development. Works across Python/FastAPI or TypeScript backends, React frontends, cloud infrastructure and container orchestration, while engaging senior client stakeholders on GenAI strategy. Requires Security Check clearance.

Department for Transport · Birmingham · £59,816 – £84,911 pa

Lead the technical delivery of AI solutions across the full product lifecycle, from design and deployment to monitoring and assurance, including classical ML and agentic/LLM-based systems. Work in a government AI and data science team, writing production Python code, running CI/CD pipelines with Terraform on GCP, and building evaluation frameworks to measure model performance.