Role OverviewWe are seeking a GPU Systems Engineer with deep expertise in CUDA programming, GPU architecture, and high-performance computing to design and optimize compute-intensive workloads on modern accelerator hardware.
What You Will Do
Design and implement high-performance CUDA kernels for compute-intensive workloads across AI and HPC use cases, profile and optimize GPU code, tune memory access patterns, and develop highly optimized libraries for linear algebra and other ML primitives.
Why It Might Be a Fit
The ideal candidate combines low-level systems mastery with strong software engineering practices, has a track record of delivering measurable performance improvements on production GPU systems, and 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, full-time, direct W2 position with Bright Vision Technologies
- Long-term, multi-year, aligned to the Bright Vision SOW delivery roadmap
- No new H1B sponsorship available, but H1B transfers welcomed for qualified candidates
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