Artificial Intelligence Jobs

Databricks · London

Customer-facing role building and productionising data and AI solutions on the Databricks platform, owning architecture and design decisions for end-to-end systems spanning data engineering, ML/AI and application development. Embeds with client teams from engineers to executives, delivering production-grade reference architectures and reusable accelerators, with around 20% travel.

Wayve · London

Hands-on role optimising inference for edge accelerators and GPUs so large transformer models run efficiently on low-cost, low-power in-vehicle compute. You'll profile model graphs, compiler/runtime behaviour and kernel execution, implement optimisations like fusion, scheduling and custom kernels, and build benchmarking and regression tests across NVIDIA Orin/Thor and Qualcomm targets, working closely with model, platform and deployment teams.

Wayve · London

Lead large-scale data enrichment and curation for the Core Model Safety team, mining hard and rare events and building workflows across pre/mid-training, reward modelling and self-supervised labelling. Design and train out-of-distribution detection mechanisms for robust driverless operation, working at the intersection of model engineering, infrastructure, compute and data.

MFK Recruitment · Brentford · £70,000 – £95,000 pa

Design and deploy production-grade computer vision systems using deep learning techniques such as CNNs and Vision Transformers, translating research into robust AI solutions for defence and security applications. Work across the full development lifecycle, from model design and training to deployment on cloud and edge platforms. Collaborate with researchers, engineers, and customers in a technically challenging environment focused on real-world autonomy and perception systems.

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.

Thought Machine · Lisbon, Portugal

Builds end-to-end features across web applications and backend services, owning requirements from engineering design through task breakdown, implementation and production debugging. Works with React, TypeScript and REST APIs in a cross-functional team of backend, front-end and full-stack engineers, with automated testing integrated throughout the development lifecycle.

Faculty · London

Lead the design, build and deployment of production-grade ML systems for national security and AI safety clients, including capability testing of frontier models. Act as a technical advisor to customers, define best practices for deploying ML at scale, and mentor junior engineers. Distinct for its focus on red teaming, evaluation and high-stakes government and frontier lab work.

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

Designs, benchmarks and optimises deep learning models for computer vision and surgical video understanding, focusing on low-latency inference on edge and cloud devices. Works with ML, platform and embedded engineers on end-to-end video pipelines, using PyTorch, TensorRT and techniques like pruning and quantization. Distinct for its operating-room, safety-critical medical imaging context.

Hays Technology · London · £100,000 – £110,000 pa

Hands-on role building the backend services, APIs and data pipelines behind a new AI layer for an investment management firm's portfolio platform. Involves LLM applications such as agent workflows, tool use and RAG, plus security controls, automated tests, AI evaluations and monitoring of accuracy, latency and cost in production.

Faculty · London

Lead the design, build and deployment of production-grade machine learning systems for clients across pharma, healthcare and other sectors. Work spans architectural decisions, scalable infrastructure, MLOps standards and mentoring junior engineers, with a strong client-facing advisory element. Requires deep Python, TensorFlow or PyTorch, and cloud plus Docker/Kubernetes experience.

Helsing · London

Builds computer vision models for object detection, recognition, classification and tracking, extending state-of-the-art architectures and running large-scale multi-GPU training on sensor data. Optimises models for real-time performance on constrained target hardware and collaborates with research, engineering and product teams to shape perception roadmaps.

Relation Therapeutics · London

Builds and scales generative and predictive models of cellular behaviour, implementing and optimising large neural networks and distributed training infrastructure. Acts as a bridge between ML research and production, profiling GPU workloads and optimising inference for use by data scientists and biologists on multi-modal biological data.

Latent Labs · London

Customer-facing engineering role deploying frontier generative biology models into pharma and biotech environments, owning the full lifecycle from technical scoping to production delivery. Involves building API integrations, data pipelines and model-serving infrastructure on AWS with Docker and Kubernetes, plus on-site work with international partners.

Tenth Revolution Group · London · £75,000 – £105,000 pa

Builds and deploys production LLM and Generative AI applications for enterprise clients, including RAG solutions, scalable data pipelines and AI-powered services. Works in a collaborative consultancy team of engineers and architects, applying software engineering best practices to take AI from proof of concept into production, with monitoring and optimisation of live systems.

Helsing · Berlin, Germany

Builds and benchmarks computer vision systems for scene matching, geo-registration, SLAM, visual odometry and 3D reconstruction, adapting state-of-the-art geometric deep learning to real-world conditions and constrained hardware. Works within a scene understanding and localisation team, collaborating across research, engineering and product to integrate outputs into navigation and decision-making pipelines.