GPU Software Engineer (CUDA)

Role Overview We are seeking a GPU Software Engineer (CUDA) to design and optimize compute-intensive workloads on modern accelerator hardware. The ideal candidate combines low-level systems mastery with strong software engineering practices, and has a track record of delivering measurable performance improvements on production GPU systems. What You Will Do Design and implement high-performance CUDA kernels, profile and optimize GPU code, tune memory access patterns, and develop highly optimized libraries for linear algebra and ML primitives. Why It Might Be a Fit The successful candidate brings strong engineering discipline, a clear communication style, and a track record of shipping meaningful work that holds up well in production. Requirements Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related field. Six or more years of experience in GPU programming and performance engineering. Deep expertise in CUDA C/C++ and GPU programming models. Strong understanding of modern GPU architectures, memory hierarchies, and execution models. Hands-on experience profiling and optimizing GPU workloads in production. Familiarity with NCCL, MPI, and high-performance interconnect technologies. Experience integrating custom kernels into ML frameworks. Strong C++ skills and familiarity with modern systems programming practices. Solid grounding in linear algebra and numerical methods. Strong communication and collaboration skills with research and engineering teams. Benefits Competitive base salary commensurate with experience, plus benefits. 100% remote work option. Long-term, multi-year employment engagement. H1B transfers welcomed for qualified candidates. No new H1B sponsorship available. Originally posted on Himalayas