Artificial Intelligence Jobs

PhysicsX · Singapore

Join a new Singapore research team building physical foundation models for industrial engineering, translating physics challenges into mathematical formulations and training deep learning models on large datasets. You will own research workstreams, run experiments, and communicate results to customers and at publication venues, with a focus on operator learning, geometric deep learning, or generative models for geometry and spatiotemporal data.

PhysicsX · Singapore

Lead technical delivery of physics-informed AI, architecting deep learning models and optimisation methods to predict and control physical systems. Own data pipelines and pre-processing best practices while mentoring a team and collaborating with simulation engineers and customers. Involves frequent on-site customer travel across multiple regions.

Faculty · London

Supports delivery of bespoke AI solutions for national security and government clients, focusing on frontier model evaluations and AI safety red teaming. Involves managing work streams, conducting open-source analysis, translating operational requirements into user stories, and designing workflows for high-stakes decision-making alongside technical teams.

Faculty · London

Supports the delivery of bespoke AI solutions for pharmaceutical and life sciences clients, managing individual work streams, analysing stakeholder requirements and translating operational needs into user stories for engineering teams. Involves open-source analysis, workflow design and testing, and close collaboration with technical teams in a small, client-facing team.

NVIDIA · United Kingdom

Lead NVIDIA's developer strategy with a major cloud service provider, driving GPU acceleration adoption across AI and generative AI workloads. The role blends developer advocacy, product management and business development, building engineering partnerships and hosting summits and meetups. High visibility with senior leadership in a strategic deep learning and HPC area.

NVIDIA · Zürich, Switzerland

Research and develop techniques to GPU-accelerate deep learning, machine learning and other AI workloads, working with technical experts to analyse and optimise complex AI and HPC algorithms on modern CPU and GPU architectures. The role also involves publishing optimisation techniques via developer blogs or conferences and influencing next-generation hardware and software design.

Anthropic · London

Leads multi-hundred megawatt power procurement and energy markets strategy for AI datacentre expansion across multiple EU jurisdictions. Builds relationships with TSOs, DSOs, regulators and ACER, structures PPAs and behind-the-meter solutions, and translates grid constraints into capacity acceleration plans.

Wayve · London

Builds ground-truth datasets and computer vision classifiers that describe complex driving scenes across Wayve's data corpus, drawing on the World Foundation Model to surface rare scenarios and performance gaps. Day to day spans defining annotation tasks and quality criteria, curating datasets, training and evaluating models in PyTorch, and integrating classifiers into enrichment infrastructure for corpus-wide inference.

Wayve · London

Lead the technical direction for an offline 3D reconstruction system that turns raw vehicle sensor data into quality-assessed 3D ground-truth geometry and ego motion. The role spans SLAM, lidar point-cloud registration, state estimation and sensor fusion, with responsibility for architecture, roadmaps, prototypes and cross-functional alignment across perception, calibration and validation teams.

Databricks · London

Customer-facing engineering role building and productionizing data and AI solutions on the Databricks platform for emerging enterprise and digital native accounts. You own architecture and design decisions, implement end-to-end systems spanning data engineering, ML/AI and application development, and embed with client teams. Billable delivery work with roughly 20% travel.

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.

The University of Manchester · Manchester · £48,337 – £59,390 pa

Develops and applies machine-learning and AI methods to protein engineering and enzyme design, analysing large biological, chemical and experimental datasets and building predictive models and computational tools. Works within an interdisciplinary group spanning the Manchester Institute of Biotechnology and Department of Chemistry, providing ML and data-science expertise, training and support to postdocs and students, and contributing to publications and funding bids.

University of Exeter · Exeter · £21,805 pa

An interdisciplinary PhD co-designing miniaturised, low-power sensing hardware with AI for field-based wildlife monitoring, including individual recognition and automated behaviour quantification. Systems are benchmarked in controlled conditions then validated on wild jackdaws and West African field sites, spanning behavioural ecology, electronic engineering and data science.

Jam Management Consultancy ltd · Reading · £35,000 – £38,000 pa

Graduate role investigating and resolving technical issues across enterprise software platforms, analysing system performance and supporting troubleshooting on cloud-based applications. Works alongside experienced engineers on analysis, testing and continuous improvement, with exposure to AI, ML, NLP, SaaS, IoT and languages including Python, C#, .NET, Java, JavaScript, TypeScript, React, C++ and SQL.

eFinancialCareers · London

Develops predictive machine learning models for fixed income and credit markets, covering issuer credit deterioration, transaction costs, liquidity forecasting and relative-value opportunities. Also builds LLM-powered document intelligence systems to extract structured data from filings, transcripts and prospectuses, with a strong emphasis on out-of-sample validation, explainability and production data pipelines.