Artificial Intelligence Jobs

Wayve · London

Lead large-scale training and post-training for Gaia, Wayve's world model that predicts future driving video and runs closed-loop with the driving stack. Own model architecture decisions, push autoregressive rollouts toward longer, more stable generation, and make the model deployment-ready. Partner with research, applications, simulation engineering and cloud teams, mentoring and setting technical direction.

Faculty · London

Serve as a high-level technical authority steering the most complex AI projects, architecting scalable large-scale systems and setting technical direction for flagship initiatives. Provide authoritative advice across business units, influence company-wide technical strategy, and act as a respected expert for internal teams and external customers in the financial services space.

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.

Wayve · London

Develop next-generation generative world models and planners such as GAIA, simulating complex driving environments for faster training and scalable deployment. Work spans diffusion and transformer architectures, latent compression, context pruning and inference-latency optimisation, with closed-loop agent interaction and sim-to-real evaluation. The role combines ML research, multi-modal modelling and production deployment, including mentoring and publishing.

PhysicsX · New York, United States

Builds and automates high-fidelity electromagnetic models across low- and high-frequency applications, from chip and package design to EMI/EMC, using tools like HFSS, Maxwell and CST. Works at the intersection of CAE and data science, generating simulation data to train ML surrogates, collaborating with customers and mentoring junior engineers.

PhysicsX · Singapore

Deliver high-fidelity multi-physics CFD simulations, from geometry clean-up and meshing to post-processing and validation against experimental data. Build parametric CAD models and automate simulation pipelines for design optimisation and DoE, generating datasets for machine learning surrogates. Partner directly with customers on-site and mentor junior colleagues.

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.

Adecco · London · £600 – £750 pd

Develops and deploys machine learning models and data pipelines that shape decision-making, customer service and business performance. Works closely with ML and software engineers on integration and coding standards, and engages stakeholders to translate complex business problems into data science solutions. Retail context with scope for personalisation, recommendation and experimentation work.

Luminance · Cambridge

Join a small, dynamic R&D team prototyping and implementing new approaches to AI problems, evaluating output quality, efficiency and feasibility against other techniques in a data-driven way. Work spans data science on large datasets, modelling and evaluation, using Python ML frameworks such as PyTorch, TensorFlow and Scikit-Learn. Open to graduates as well as senior candidates with published work in NLP, Computer Vision or Deep Learning.

University of Essex · Ipswich · £40,000 – £45,000 pa

A KTP Associate role embedded at Distag QCS in Ipswich, working with a large, messy ERP dataset never designed for machine learning. The post holder shapes the data, builds reliable models, and leads the introduction of data-driven decision making in a business with no existing in-house data science capability. It blends hands-on Python development with change management, communication and academic paper contributions.

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.

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.

Isomorphic Labs · London

Research engineers translate frontier research concepts into practical implementations, building and optimising state-of-the-art AI models such as Transformers, GNNs and diffusion models, plus the codebases, data pipelines and infrastructure for training and evaluation. They design and run experiments, analyse model performance, and advise on bringing models to production, working closely with research scientists in a cross-disciplinary team.

McGregor Boyall · London · £115,000 pa

Hands-on role designing, developing and deploying production-grade Generative AI and Agentic AI solutions within a global technology consultancy's Data & AI practice. Combines Data Science and Machine Learning foundations with modern software engineering, including Python APIs, microservices, RAG architectures, vector databases and MLOps, while influencing solution architecture and working directly with clients on AI transformation projects.

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.