11 of 11 CUDA Jobs in Cambridge

software on GitHub, PyPI, Anaconda Cloud, and Docker Hub, as well as use of Pytorch lightning, Git, test-driven design. Knowledge of parallel computing technologies, such as NVIDIA's CUDA platform, OpenCL, and OpenMPI. The salary range for Cambridge, UK: - Senior Scientist I, Computational Biology: £75,000 - £117,500 Senior Scientist II, Computational Biology: £94,000 - £152,500 Exact More ❯

engineering principles to ensure robust, maintainable solutions. PREFERRED EXPERIENCE: GPU Kernel Development & Optimization: Proficient experienced in designing and optimizing GPU kernels for deep learning on AMD GPUs using HIP, CUDA, and assembly (ASM). Strong knowledge of AMD architectures (GCN, RDNA) and low-level programming to maximize performance for AI operations, leveraging tools like Compute Kernel (CK), CUTLASS, and More ❯

numerical calculation, compilation, algorithm and chip co-design, runtime, or shared memory Strong background in software development using C/C++ and Python Skilled with GPU compute APIs (e.g., CUDA, OpenCL), deep learning frameworks, and compilers Familiarity with AI models, algorithm trends, and translating application requirements into chip-level solutions Experience with GPU acceleration, inference backends, and frameworks such More ❯

engineering principles to ensure robust, maintainable solutions. PREFERRED EXPERIENCE: GPU Kernel Development & Optimization: Proficient experienced in designing and optimizing GPU kernels for deep learning on AMD GPUs using HIP, CUDA, and assembly (ASM). Strong knowledge of AMD architectures (GCN, RDNA) and low-level programming to maximize performance for AI operations, leveraging tools like Compute Kernel (CK), CUTLASS, and More ❯

large language models, efficient computing based on low-precision arithmetic, deep learning models including large generative models for language, vision and other modalities . Experience writing C Triton/CUDA kernels for performance optimisation of ML models. Have contributed to open-source projects or published research papers in relevant fields. Knowledge of cloud computing platforms. Keen to present, publish More ❯

CUDA Kernel Developer £80,000 - £90,000 + bonus & hybrid working! I'm currently working with a Cambridge-based, multinational Semiconductor scale-up who are focused on developing AI accelerators. You will have the opportunity to work in a rapidly changing environment where your new ideas will become innovative products, services, and customer experiences. They are a successful, growing … business, offering the chance for an engineer to progress their career and achieve future aspirations. They provide a stable and supportive environment. They are looking for a CUDA Kernel Developer to develop and optimise high-performance kernels for ML operators on NPU architectures. They are looking for an exceptional engineer to join a talented team of 5 engineers at … and accelerators specialised for Ai applications. You will also collaborate with the hardware and software teams to integrate kernels into the NPU framework. What's required for a successful CUDA Kernel Developer? Extensive experience in kernel development projects for GPUs Involvement in OpenCL, CUDA or similar parallel programming languages Understanding of ML frameworks - TensorFlow, PyTorch etc Strong C++ More ❯

and architecture of GPU IPs - Graphics Hardware Processors (5 - 10+ years' experience) Strong understanding of modern 3D graphics and/or compute APIs, such as Vulkan, D3D12 and OpenCL, CUDA etc. Definition of high-level GPU architecture/micro-architecture Confidence knowledge in the ASIC digital design flow Experience in R&D of the latest products and features Ability More ❯

and hands-on experience with frameworks like PyTorch, TensorFlow, or JAX Experience building ML models in unique settings (e.g., constrained hardware or novel data) Familiarity with GPU processing (e.g., CUDA) and a range of ML techniques Bonus if you’ve worked in a client-facing or consultancy setting Next Steps This Machine Learning Consultant role is generating a lot More ❯

top degree in a STEM subject UK nationality Experience deploying machine learning on hardware, from embedded systems to edge computing, is desirable. Knowledge of GPU programming languages and frameworks (CUDA, ROCm, etc.) is also a plus. Your future colleagues are highly skilled professionals from diverse industry backgrounds, fostering a low-management, team-oriented environment that values individual expertise. Benefits More ❯

deploying machine learning onto a range of hardware from resource constrained embedded systems through to edge computing is desirable. As is any knowledge of GPU programming languages and frameworks (CUDA, ROCm, etc). Your future colleagues will be similarly highly skilled, with experience across industry and the drive to innovate. You will find yourself in a low-management work More ❯

deploying machine learning onto a range of hardware from resource constrained embedded systems through to edge computing is desirable. As is any knowledge of GPU programming languages and frameworks (CUDA, ROCm, etc). Your future colleagues will be similarly highly skilled, with experience across industry and the drive to innovate. You will find yourself in a low-management work More ❯