Artificial Intelligence Jobs

• New York, United States
• Hybrid
• US$150,000 – US$250,000 pa
• Senior

Builds and deploys customer-facing applications on top of physics AI models, working directly with clients, data scientists and ML engineers. Involves full-stack work: FastAPI REST APIs and Python microservices, plus cloud deployment with Helm, Kubernetes, Terraform and AWS/Azure. Expect on-site travel to customer sites for 3-4 weeks per quarter.

FastAPI · Helm · Kubernetes +3

• New York, United States
• Hybrid
• US$150,000 – US$190,000 pa
• Mid-level

Delivery-focused role embedding physics-aware AI models into customer tools, working on-site with clients across aerospace, automotive and energy. Involves building reliable ML data pipelines, manipulating 3D point-cloud and mesh data, and translating R&D outputs into reusable libraries and products. Expects travel of 3-4 weeks per quarter to customer sites worldwide.

TensorFlow · MLflow · Spark +6

• London
• £18,000 pa
• Entry level
• Contract

Develops an AI-enabled decision-support framework combining building-performance simulation, machine learning, GIS and remote sensing to optimise green roofs and façades for energy, carbon and thermal performance. Primarily computational, with no routine lab or fieldwork, and scope refined with the successful candidate.

GIS

• Cranfield
• £21,805 pa
• Entry level
• Contract

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.

AI-on-RAN · 6G

• Oxford
• £21,805 pa
• Entry level
• Contract

Investigates how the rapid growth of AI can be supported by more sustainable, circular hardware and infrastructure, linking computational performance to the physical materials and equipment required. Develops scenarios for UK AI and data centre growth, mapping hardware requirements to critical raw materials and modelling how lifetime extension, reuse, repair and remanufacture could cut environmental impacts. Based in the Circular Economy and Sustainability Lab, contributing to the Circular Electricals and Electronics Project.

Data Centres

• London
• £23,805 pa
• Entry level
• Contract

Develop a framework combining a differentiable reacting flow solver with a machine learning-based controller to anticipate and mitigate extreme events such as flashback and thermoacoustic instabilities in hydrogen and SAF combustion. The role sits within the European CONTEXT project, using high-fidelity simulations and Imperial's HPC facilities, with applications spanning novel actuators like spray water injection and electrically-driven droplet control.

HPC

• Nottingham
• Hybrid
• £21,805 pa
• Entry level
• Contract

A fully funded four-year PhD developing thermodynamic and transient models of hybrid energy systems combining gas turbines, carbon capture, biomass gasification and solar thermal. The work covers techno-economic and life cycle assessment plus AI-driven optimisation and control, with a three-month industrial or policy placement through the Net2Zero CDT.

MATLAB · Python · Aspen Plus +2

• New York, United States
• Hybrid
• US$200,000 – US$250,000 pa
• Senior

Owns deployment of ML models and engineering surrogates (deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, optimization) into customer production environments, building scalable training and inference pipelines and APIs on cloud and on-prem. Leads scoping and architecture design, mentors engineers and data scientists, and travels to customer sites roughly 3-4 weeks per quarter to embed AI models on-site.

Python · PyTorch · Pandas +3

• New York, United States
• Hybrid · 2–3 days in office
• US$120,000 – US$240,000 pa

Builds and deploys deep learning and probabilistic models to predict and control physical systems, working alongside simulation and ML engineers. Owns data pipelines and production deployment, and collaborates directly with customers on-site across multiple regions. Based in Manhattan with 2-3 days per week in office and frequent travel.

NumPy · SciPy · Pandas +2

• New York, United States
• US$150,000 – US$250,000 pa

Builds and deploys customer-facing applications that put physics AI models into production, working directly with customers, data scientists and ML engineers. Involves rapid prototyping, RESTful APIs in Python (FastAPI), microservices, and cloud deployment with Kubernetes, Helm, Terraform and AWS/Azure, plus 3-4 weeks of travel per quarter to customer sites.

FastAPI · Helm · Kubernetes +3

• New York, United States
• Hybrid
• Lead

Lead the ML approach to manufacturing and MRO data, taking models from design through deployment in customer production environments across cloud, on-prem and edge. Work with sparse, drifting sensor and process data, fusing physics simulation with shop-floor measurement, and set uncertainty quantification and validation standards. Mentor engineers and data scientists while travelling to customer sites roughly 3-4 weeks per quarter.

Python · PyTorch · Pandas +3

• San Francisco, United States
• Hybrid
• US$150,000 – US$190,000 pa

Builds and deploys machine learning pipelines for industrial physics applications, working directly with customers on-site to embed AI models into practical tools. Involves manipulating 3D point-cloud and mesh data, cloud and HPC infrastructure, and translating R&D outputs into reusable libraries and products.

TensorFlow · MLflow · Spark +6