Machine Learning Jobs

• Singapore
• Senior

Build and deploy customer-facing applications that put physics AI models into production, working directly with customers, data scientists and ML engineers. The role spans rapid prototyping, backend development of Python/FastAPI REST APIs and microservices, and cloud deployment using Kubernetes, Helm, Terraform and AWS/Azure. It suits someone who can grasp complex engineering problems across industries and own solutions end-to-end.

FastAPI · Helm · Kubernetes +3

• New York, United States
• Hybrid
• US$240,000 – US$300,000 pa
• Director · manages people

Leads regional deployment engineering for a physics AI platform, owning end-to-end delivery into customer-owned infrastructure and acting as primary technical contact for CIOs and CTOs. Combines executive engagement with hands-on work on Kubernetes, cloud and infrastructure-as-code deployments, while hiring and scaling a team of deployment engineers. Requires navigating regulated, high-security and on-prem/HPC environments.

Kubernetes · AWS · Azure +6

• London
• Hybrid
• Senior
• Permanent

Owns embedded software that connects an autonomous driving AI to vehicle platforms, building integration and adaptation layers across hardware. Works on inference integration, vehicle data, navigation, localisation and motion control interfaces, taking features from design through HIL and vehicle testing. Requires strong modern C++ and Linux/QNX experience on Nvidia and Qualcomm platforms.

Nvidia · Qualcomm · Linux +3

• London
• Hybrid
• Senior
• Permanent

Lead large-scale data enrichment and curation for the Core Model Safety team, collaborating across pre/mid-training, reward modelling and self-supervised labelling. Build workflows for hard and rare event mining, design out-of-distribution detection for driverless operation, and improve ML operations efficiency across model engineering, infrastructure and compute.

PyTorch · CUDA · VLM +1

• United Kingdom
• Hybrid
• Senior

Designs, builds and tests intelligent systems for defence and security clients, covering signal processing, radar, computer vision, transformers and edge AI. Takes technical ownership of significant project parts, mentors junior engineers, and works directly with clients on proposals and new work. Requires SC clearance and substantial time on-site.

Transformers · Edge AI

• Hatfield
• Hybrid
• Entry level
• Temporary

Two-year rotational graduate scheme with four six-month placements across Ocado's technology division, spanning bot software and hardware, eCommerce, fulfilment control systems, and data science. Graduates work in teams on robotics, ML, and warehouse automation challenges, gaining broad exposure before moving into a long-term role.

• United Kingdom
• Remote
• Senior

Design, develop and optimise GPU/CPU-accelerated numerical libraries such as DALI and nvImageCodec, with heavy focus on performance tuning, benchmarking and CUDA-based parallel algorithms. The role also involves setting technical roadmaps with partners and providing technical leadership and guidance to other library engineers.

CUDA · DALI · nvImageCodec +1

• Switzerland
• Remote
• Senior

Design, develop and optimise GPU/CPU-accelerated numerical libraries such as DALI and nvImageCodec, with heavy focus on performance tuning, benchmarking and CUDA-accelerated algorithms. The role also involves setting technical roadmaps with partners and providing technical leadership to other library engineers.

CUDA · DALI · nvImageCodec +1

• Tokyo, Japan
• On-site
• Shift work

On-site systems support role in Tokyo, monitoring business systems and resolving logged incidents to keep Ocado's automated grocery operations running. Works within a shift team covering 24x7 operations, handling bot recoveries, failed tasks, pick support issues and hardware, software and networking faults while liaising with engineering and other technology teams.

• Solihull
• £45,000 – £62,000 pa
• Permanent

Research and develop AI/ML approaches for power electronics, designing, modelling and simulating converter systems (AC/DC, DC/DC, DC/AC) using tools such as MATLAB, PLECS or Ansys. The role sits at the intersection of power electronics and artificial intelligence, translating academic research into practical engineering applications across electric vehicles, rail and renewable energy.

MATLAB · PLECS · Ansys

• Oxford
• On-site
• £39,424 – £47,779 pa
• Entry level
• Contract

Two postdoctoral roles in the Visual Geometry Group, each tied to a separate project funded by Toyota Motor Europe or Amazon. One develops deep reinforcement learning and computer vision for robust visuomotor policies transferring to real robots; the other studies 3D geometry and motion representations for vision-language-action robotic manipulation, including deformable objects, with evaluation on real hardware.

RoboSim

• London
• Hybrid
• Senior
• Permanent · Part time

Lead the computationally guided design of a lipid nanoparticle delivery platform, applying chemical and biophysical principles to optimise LNP composition and formulation. Use AI-enabled chemistry, cheminformatics, predictive models and molecular modelling to prioritise formulation components, working closely with the experimental team and founding team in a small start-up.

• London
• Hybrid · 1 day in office
• £195,000 – £245,000 pa
• Senior

Conducts empirical research on AI's economic effects, building and extending the Anthropic Economic Index with regionally-specific analysis. Develops novel measurement methodologies using econometrics, machine learning, and structural estimation, and engages governments, academia, and industry partners to translate findings into policy recommendations.

Claude

• 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 at the intersection of scientific machine learning and fluid dynamics, using high-fidelity simulations and Imperial's HPC facilities.

HPC

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

Develops a multiscale Scientific Machine Learning digital-twin framework to predict thermal trajectories, torque capability and efficiency in low-speed, high-torque electric propulsion. Combines physics-informed neural networks, neural state-space models and Neural ODEs, validated through safety-constrained dynamometer experiments at the Centre for Future Clean Mobility and on-site work with a marine power-systems partner.

Neural Ordinary Differential Equations · Deep Neural Networks · Recurrent Neural Networks +1