Artificial Intelligence Jobs

Faculty · Remote (UK)

Lead backend and edge/IoT engineering for high-stakes Defence projects, bridging proof-of-concept work and robust production systems. You will mentor a squad of engineers, design complex components, and build CI/CD and containerisation pipelines with Docker and Kubernetes while shipping Python and compiled-language code alongside ML engineers and data scientists.

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.

PhysicsX · Singapore

Build and deploy customer-facing applications powered by physics AI models, working directly with customers, data scientists and ML engineers. Involves rapid prototyping, Python/FastAPI microservices, and cloud deployment with Kubernetes, Terraform and AWS/Azure, plus quarterly travel to customer sites.

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.

Wayve · London

Lead a team of ML engineers and applied scientists building synthetic data from generative world models like GAIA-3, turning them into a production engine for training-grade driving experience. Own the loop end to end, from checkpoint and large-scale GPU inference to artefacts landing in driving-model training, while setting technical direction on rig transfer, pose transfer and controllability.

Relation Therapeutics · London

Design and implement generative models that learn intervention effects from single-cell perturbation and multiomic data, focusing on counterfactual prediction, generalisation and experimental design. Work in interdisciplinary teams with experimental biologists to validate computational hypotheses and guide the highest-signal next experiments, using modern ML tooling including agentic workflows.

Darktrace · Cambridge

Conducts independent and collaborative research into language models, neural networks, statistical methods and classical machine learning, prototyping new ideas and improving existing projects. Implements models into the wider software stack, including optimised solutions for edge devices with tight latency and memory constraints, working closely with software engineers and security analysts.

University of Sheffield · Sheffield · £32,080 pa

Build and evaluate machine learning models that predict Strep A outbreak risk from multiple real-world datasets, turning them into early-warning signals. Work with clinicians and an engineering team so analyses feed into a practical public health tool, with a focus on reproducible Python and/or R analysis.

Adria Solutions · Huddersfield · £55,000 – £70,000 pa

Develops software and applied AI models for machine vision, working across C++, C# and Python to build image-processing algorithms and integrate models into reliable applications. Involves dataset preparation, model evaluation, performance tuning for accuracy and inference speed, automated testing and debugging of vision pipelines. Hybrid or remote, with a path to lead an AI team.

Adria Solutions · Huddersfield · £55,000 – £65,000 pa

Develops software and applied AI models for machine vision, working across C++, C# and Python to build image-processing algorithms and integrate models into reliable applications. Covers dataset preparation, model evaluation, performance tuning and automated testing, with a focus on accuracy, inference speed and maintainable code.

University of Oxford · Oxford · £49,119 – £59,955 pa

Leads a research strand on Bayesian methods for evaluating and monitoring AI systems, publishing findings, running the lab's open-source software, producing policy-facing outputs, and guiding research assistants and students. Based in the Bayesian Governance Lab within Oxford's Department of Engineering Science, in collaboration with the Oxford Martin AI Governance Initiative, on a two-year fixed-term post.

Aioi Nissay Dowa Europe · Oxford · £81,322 – £112,488 pa

This role involves leading research in privacy-preserving generative AI, focusing on techniques like differential privacy, federated learning, and secure inference. The scientist will design and validate machine learning models, translate research into deployable systems, and contribute to publications and collaborations within a multi-partner environment. Emphasis is placed on responsible AI, reproducibility, and mentoring junior team members.

Darktrace · Cambridge

Conducts independent and collaborative research across large language models, statistical methods and classical machine learning, prototyping ideas and implementing models into the wider software stack. Produces optimised solutions for latency and memory, including deployment on edge devices, working closely with software engineers and security analysts.

Rise Technical Recruitment · Solihull · £45,000 – £62,000 pa

Research role applying AI and machine learning to the design, simulation and optimisation of power electronic converter systems, including AC/DC, DC/DC and DC/AC technologies. Working with experienced engineers and researchers, you develop models, algorithms and tools using MATLAB, PLECS or Ansys, and help translate academic research into practical engineering applications across electric vehicles, rail and renewable energy.

eFinancialCareers · London

Lead the build-out of a hedge fund's machine learning function, defining research strategy and hiring a team of ML researchers and engineers. Directs work in deep learning, reinforcement learning, probabilistic and time-series modelling, and generative AI, partnering with quant and investment teams on alpha generation, forecasting, portfolio construction, risk and execution. Combines hands-on technical direction with strategic leadership.