Artificial Intelligence Jobs

PhysicsX · London

Builds and validates high-fidelity multiphase CFD and coupled CFD-DEM models, covering geometry clean-up, meshing, simulation, post-processing and experimental validation for granular and particle-laden systems. Automates parametric CAD and simulation pipelines for design optimisation and DoE, generating datasets for ML surrogate models on cloud and HPC resources, while working on-site with customers and mentoring junior colleagues.

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.

Deerfoot Recruitment Solutions · Didcot · £700 – £900 pd

Architect and build multi-agent AI systems end-to-end, combining frameworks like LangGraph or Haystack with bespoke orchestration, state management and tool-calling logic. Embed LLMs and vision-language models into live reasoning, search and task-execution workflows, deploying across cloud and on-premises environments with monitoring, evaluation and guardrail tooling. Set technical standards for agentic AI within the team, working with a biotech and pharma customer.

Wayve · London

Builds reusable Python libraries and platform tooling for multimodal data loading, distributed training, inference, checkpointing and observability, supporting ML teams running models across thousands of GPUs. Partners closely with researchers to turn complex workflows into stable, scalable software, leading projects from discovery to delivery. A software and platform engineering role rather than ML modelling.

Palo Alto Networks · London

Design and build software solving Workload Identity challenges across client and server, from prototyping to production. The role spans networking, security, authorization, SDKs, cloud and Kubernetes, with scope to lead and mentor a close-knit team and shape product direction with stakeholders.

Darktrace · Cambridge

Works within Cambridge R&D teams on high-impact projects spanning rapid prototyping and structured platform development, providing expert technical direction and mentoring engineers across languages such as Python, JavaScript, Rust and C++. Involves advancing methodology for defending against unknown cyber-attacks, shaping technical strategy, and engaging with executive leadership. Hybrid role with two days a week in the Cambridge office.

Darktrace · London

Works within the Cambridge R&D teams on high-impact projects spanning rapid prototyping and structured platform development, advancing methodology for defending against unknown cyber-attacks. Provides expert technical direction, mentors engineers across languages like Python, JavaScript, Rust and C++, and engages executive leadership on technical strategy. Requires Docker, cloud, CI/CD and Git proficiency with a strong interest in cyber-security and malware forensics.

Faculty · London

Deliver bespoke, production-grade machine learning systems for government and national security clients, covering the full ML lifecycle from scoping and architecture to deployment. Work with Python, Scikit-learn, TensorFlow or PyTorch, plus cloud platforms and Docker/Kubernetes, while advising stakeholders and defining standards for deploying ML at scale.

Faculty · London

Deliver bespoke, production-grade machine learning systems for government and national security clients, spanning the full ML lifecycle from architecture to deployment. Work with Python, Scikit-learn, TensorFlow or PyTorch, plus cloud platforms and Docker/Kubernetes, while advising stakeholders and setting deployment standards.

Amtis Professional · Birmingham · £80,000 – £90,000 pa

Architect end-to-end enterprise AI solutions spanning data, knowledge and process layers, covering internal processes, reporting, frontline operations and customer experience. Design and validate proof-of-concept solutions, define target architectures and reusable patterns, and lead MLOps and model deployment pipelines for LLMs, agentic and generative AI. Work hybrid in the West Midlands across IT, data, security and business teams to move PoCs toward production.

OpenAI · London

Builds and scales the infrastructure that trains and deploys AI agents, spanning a novel in-house container orchestration platform, FastAPI and gRPC APIs, and Terraform-managed cloud systems. Works closely with researchers on large-scale training runs and with product teams launching agentic products to hundreds of millions of users.

Ocado · London

Owns the software engineering that brings data science and machine learning products into live production for the Autoplanner team, building AI-powered planning systems across global warehouses and last-mile assets. Writes typed, well-tested Python (with some Java for OSP integration), builds APIs and data contracts, manages AWS deployments and CI/CD, and packages, serves and monitors ML models. Acts as engineering partner to data scientists and shares on-call support.

Latent Labs · London

Architect novel generative models to design functional proteins, working in an interdisciplinary team of ML researchers, protein engineers and biologists. The role spans data curation, evaluation metrics, rapid prototyping, cloud training/inference optimisation and planning wet lab testing campaigns, with about 10% of time for self-development.

Causaly · London

Builds and operates the platform running long-lived agentic workflows, where a single run can last hours and fan out across dozens of subagents. Work spans durable execution, checkpointing and retries, LLM integration with guardrails, and tracing and cost attribution across services and two languages, weighted towards backend and platform in TypeScript and Node.js.

Causaly · London

Builds and operates the platform running long-lived agentic workflows in production, where a single run can last hours and fan out across dozens of subagents. Work spans durable execution, checkpointing and retries, LLM integration with guardrails, and tracing and cost attribution across services and two languages, with a backend and platform weighting in TypeScript and Node.js.