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.
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