21 jobs for “algorithm”
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.
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.
Relation Therapeutics London
Builds and scales generative and predictive models of cellular behaviour, acting as the bridge between ML theory and implementation. Day to day involves optimising large neural networks, distributed multi-GPU/multi-node training, profiling GPU workloads, and productionising research code for multi-modal biological data.
TTP Cambridge
Consultants design and deploy machine learning systems for diverse defence and security projects, from proofs-of-concept to working prototypes. The role spans literature analysis, model training, rapid prototyping and experiment design, often combining science, engineering and ML in novel settings. Work is on-site in Cambridge within a flat, collaborative team of around 40 specialists.
Anthropic London
A four-month, full-time research fellowship working on empirical AI projects in either ML systems/performance or reinforcement learning, using external infrastructure like open-source models and public APIs. Fellows receive direct mentorship from Anthropic researchers and aim to produce a public output such as a paper submission, with projects spanning CPU simulators, accelerator backends, synthetic data pipelines, and RL environments.
