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