Artificial Intelligence Jobs

PhysicsX · London

Owns deployment of ML models and engineering surrogates (deep learning on CAE/CFD/FEA data, forecasting, anomaly detection) into customer production environments, building scalable training and inference pipelines with Python, PyTorch, Kubeflow and fastAPI. Leads scoping and architecture, mentors engineers, and travels to customer sites roughly 3-4 weeks per quarter.

PhysicsX · Singapore

Lead the deployment of ML models and engineering surrogates—deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, and optimisation—into customer production environments. Own scoping, architecture, and success metrics for data/ML systems built with Python, PyTorch, Pandas, fastAPI, Scipy, and Kubeflow across cloud and on-prem. Mentor engineers and data scientists while travelling 3-4 weeks per quarter to customer sites worldwide.

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.

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.

Wayve · London

Owns the engineering release process for autonomous driving models, defining branching strategies, release cadence, configuration management and quality gates. Reviews model, architecture and code changes against intended outcomes, assesses evaluation results and builds CI/CD tooling and observability to deliver ML systems reliably at scale.

Faculty · London

Set technical direction for complex AI/ML projects, leading delivery of large-scale platforms in high-risk national security environments. Define roadmaps across multiple workstreams, justify architectural decisions to senior stakeholders, and coach engineers while building shared deployment and CI/CD infrastructure. Requires DV eligibility and occasional on-site client work.

Ocado · Kraków, Poland

Senior ML engineer role in a cross-craft data science team building prediction, ranking and personalisation systems for an e-commerce platform. Owns the full ML lifecycle on production systems, from experimentation and training through serving, monitoring and MLOps, while coaching others and shaping reusable platform building blocks.

NVIDIA · Cambridge

Develops algorithms and optimizations for NVIDIA's LPX inference and compiler stack, building high-performance runtime and compiler components for end-to-end inference. Involves mapping large-scale neural network workloads onto future hardware, working with LLVM/MLIR, and collaborating with hardware architects on codesign. Hybrid role based in Cambridge.

SoCode · Cambridge · £50,000 – £80,000 pa

Develops intelligent embedded systems using Python, C and C++, applying machine learning and computer vision to real-world products. Works with microcontrollers, sensors and connected hardware, designing software architectures and delivering production code while collaborating directly with clients from concept to finished product.

AECOM · London

Lead the design and deployment of applied machine learning models for infrastructure and engineering, owning the full lifecycle from problem formulation to production iteration. Work spans optimisation, simulation and scientific ML, partnering with MLOps, software and domain experts to embed AI into a SaaS platform, with mentoring and technical leadership duties.

NVIDIA · United Kingdom

Develops algorithms and optimizations for NVIDIA's LPX inference and compiler stack, building high-performance runtime and compiler components and mapping large-scale inference workloads onto future hardware. Works at the intersection of compilers, systems and deep learning, using LLVM/MLIR and frameworks like PyTorch and TensorFlow, and collaborates with hardware architects on codesign.

Isomorphic Labs · London

Builds greenfield machine learning models and algorithms for drug discovery, designing new architectures, running experiments, and scaling training and inference frameworks. Works in an interdisciplinary team of ML scientists and domain experts, with opportunities to lead projects and mentor others depending on experience.

Cranfield University · Cranfield · £21,805 pa

A PhD studentship researching AI-on-RAN, optimising distributed and mobile inference of large language models by adapting token, memory and bandwidth use in real time. The work spans AI and telecoms, with cross-university FTH training and exposure to defence, government and infrastructure stakeholders, aiming to shape 6G network design.

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.

University of Sheffield · Sheffield · £39,560 – £43,099 pa

Postdoctoral role applying explainable NLP and machine learning to analyse online disinformation narratives, integrate findings into a user-facing verification toolkit, and evaluate commercial chatbots and AI-generated search overviews. The researcher joins the European-funded ANTIGONE project, collaborating with multidisciplinary partners and leading publication of results in high-impact journals and conferences.