Machine Learning Jobs

Cambridge Consultants · United Kingdom

Take technical ownership of AI projects for defence and security clients, designing and building agentic systems that search, interpret and act on information. Lead smaller projects, mentor junior engineers, and work directly with clients on proposals and new work. Requires SC clearance and UK residency.

Cambridge Consultants · United Kingdom

Senior technical role architecting agentic AI systems for defence and security clients, acting as technical lead on complex projects and setting departmental technical direction. Involves hands-on engineering in Python, client-facing proposal work, mentoring engineers and conducting technical interviews. Requires SC security clearance and UK residency.

NVIDIA · United Kingdom

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.

NVIDIA · Switzerland

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.

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, engineers and domain experts, with opportunities to lead projects and mentor others depending on experience.

Cambridge Consultants · United Kingdom

Graduate role working on client assignments across embedded systems, spanning analogue and digital hardware, FPGA design, PCB layout and embedded software in C, C++ or Rust. You'll join a multi-disciplinary team, interact directly with clients through requirements capture to handover, and work on projects from consumer devices to defence and national security.

Cambridge Consultants · United Kingdom

Work as part of a multi-disciplinary technical team on client assignments spanning consumer devices, industrial systems, and defence. Design and implement embedded systems, including C software for embedded targets, SystemVerilog for FPGAs, PCB design, and hardware testing, while interacting directly with clients from requirements capture to handover.

Cambridge Consultants · United Kingdom

Work on multidisciplinary engineering projects across consumer, industrial, and defence sectors, designing embedded systems, writing firmware in C or SystemVerilog, and developing hardware for innovative products. Engage in full project lifecycles from requirements to handover, with mentorship to grow technical and systems design expertise. Projects include robotics, AI-driven security solutions, and collaborative product development with major clients.

NVIDIA · Bristol

Research and develop techniques to GPU-accelerate leading high performance computing applications across scientific computing, computational engineering and data science. The intern performs in-depth analysis and optimisation for current and next-generation GPU architectures, working with application developers and collaborating with architecture, research, libraries, tools and system software teams.

NVIDIA · Zürich, Switzerland

Research and develop techniques to GPU-accelerate leading high performance computing applications across scientific computing, computational engineering and data science. The intern performs in-depth performance analysis and optimisation for current and next-generation GPU architectures, working directly with application developers and collaborating with architecture, research, libraries, tools and system software teams.

NVIDIA · Cambridge

Design and optimize compiler technologies for NVIDIA's CPUs, focusing on hardware-software co-design to enhance performance for AI and high-performance computing workloads. Collaborate with distributed teams and open-source communities to develop next-generation compiler toolchains. Analyze real-world AI and HPC applications to drive improvements in both hardware and software stacks.