Artificial Intelligence Jobs in London

Synthesia · UK Remote

Shape how the company shows up in experiential moments worldwide, designing booths, spatial environments, signage, print and merchandise from concept to production. Develop cohesive event identities across physical and digital touchpoints, storyboard motion content for keynotes, and art-direct external vendors. Works in a small senior brand design team with low process and high ownership, requiring travel across Europe and the US.

PhysicsX · London

Owns and evolves an HPC environment for CPU/GPU-heavy physics simulations, covering cluster administration, job scheduling (Slurm/PBS/LSF), performance tuning and capacity planning. Acts as escalation point across HPC, developer tooling and general IT support, mentors junior engineers, and drives automation-first, zero-trust infrastructure in a scale-up.

PhysicsX · Singapore

Customer-facing role owning the full customer journey, from onboarding and change management to roadmap planning and contract preparation. Works alongside simulation, software, ML engineers and data scientists to translate industry challenges into product opportunities, tracking engagement and measuring value. Based in Singapore, bridging advanced AI capabilities and practical engineering applications.

Faculty · Remote (UK)

Deliver bespoke, production-grade machine learning systems for defence clients, covering the full ML lifecycle from architecture and scoping to deployment. Work with Python, Scikit-learn, TensorFlow or PyTorch, plus cloud platforms and Docker/Kubernetes, splitting time between client sites and remote work.

Faculty · Remote (UK)

Sets technical direction for complex, business-critical AI projects in the defence sector, architecting production-grade machine learning solutions and overseeing end-to-end delivery. Balances speed, innovation and reliability while mentoring data scientists and acting as a trusted technical advisor to demanding clients. Requires UK Security Clearance eligibility and 2-4 days per week on-site with customers.

Medtronic · London · £76,800 – £115,200 pa

Designs, builds and maintains AWS and on-prem infrastructure used by ML engineers, data scientists and product teams, with a strong focus on Kubernetes, Helm, Terraform/OpenTofu and GitOps delivery. Also handles platform service requests, incident diagnosis and reliability improvements, working across engineering teams in a surgical AI centre of excellence.

Darktrace · Cambridge

You will prototype and develop new ideas to improve Darktrace's cybersecurity services, balancing creativity with time constraints while collaborating with a cross-functional team of engineers, designers and strategists. Work spans rapid prototyping and structured platform development, with a primary focus on TypeScript alongside Docker and cloud environments.

Darktrace · Cambridge

Contributes to security research projects spanning rapid prototyping and open-ended initiatives, with a focus on generative AI security and attacker tradecraft. Investigates threats such as prompt injection, poisoning and extraction attacks, and provides feedback to product, development and machine learning teams. Hybrid role requiring two days a week in the London or Cambridge office.

Medtronic · London · £76,800 – £115,200 pa

Develops high-performance, low-latency video and AI processing pipelines for use in the operating room, leveraging hardware acceleration for capture, inference, visualisation and streaming. Works in a multidisciplinary team on robust, safe-by-design medical device software, with a strong C++17-23, multi-threading and real-time video focus.

eFinancialCareers · London · £70,000 – £125,000 pa

Builds and evolves production backend systems in Go for a start-up's agentic development platform, with some work in React and TypeScript. Collaborates closely with Product, Design and other engineers, contributing to design and code reviews while solving complex technical problems. Fully remote within the UK, with a strong emphasis on hands-on engineering and LLM or agentic workflow experience.

eFinancialCareers · London

Leads a global legal and professional services firm's AI and data agenda, translating strategy into a delivery programme that moves initiatives from experimentation to sustainable adoption. Works across legal, fiduciary and business services divisions on productivity, decision-making and client outcomes, reporting to the Director of Service Innovation and managing AI and data delivery teams through matrix leadership.

Softweb Resourcing · London · £120,000 – £180,000 pa

First dedicated AI hire at a profitable early-stage video startup, owning AI engineering end-to-end and shaping product quality, infrastructure efficiency and technical direction alongside the founders. Work spans applied AI/ML/MLOps, building eval frameworks for non-deterministic outputs, and running frontier LLMs and agentic workflows in production at scale.

Anthropic · London · £265,000 – £375,000 pa

Paid, fixed-term research residency of six weeks to six months for people transitioning into empirical AI safety work, with a scoped project and direct mentorship from Anthropic researchers. Residents get access to Claude models and GPU compute and work on areas such as scalable oversight, interpretability, adversarial robustness, AI control, safeguards, and frontier red-teaming.

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.

Wayve · London

Builds ground-truth datasets and computer vision classifiers that describe complex driving scenes across Wayve's data corpus, drawing on the World Foundation Model to surface rare scenarios and performance gaps. Day to day spans defining annotation tasks and quality criteria, curating datasets, training and evaluating models in PyTorch, and integrating classifiers into enrichment infrastructure for corpus-wide inference.