Remote GPU Systems Engineer - CUDA & HPC Expert

Bright Vision Technologies; Issaquah (WA); On-site; USD 100,000 - 150,000; Full time

Job summary

Bright Vision Technologies is seeking a GPU Systems Engineer to design and optimize compute-intensive workloads on modern accelerator hardware. You will deliver high-performance CUDA kernels, profile using Nsight tools, and collaborate with cross-functional teams to translate requirements into engineered solutions.

The role focuses on AI training, inference, scientific computing, and high-throughput data processing, with a strong emphasis on performance, reproducibility, and scalable

Qualifications

• Six or more years of experience in GPU programming and performance engineering.
• Deepexpertisein CUDA C/C++ and GPU programming models.
• Strong understanding of modern GPU architectures and memory hierarchies.
• Hands-on experience profiling and optimizing GPU workloads in production.

Responsibilities

• Design and implement high-performance CUDA kernels for compute-intensive workloads across AI and HPC use cases.
• Profile and optimize GPU code using Nsight Systems, Nsight Compute, and CUDA profilers.
• Tune memory access patterns, occupancy, register usage, and shared memory utilization for peak performance.
• Develop highly optimized libraries for linear algebra, attention, and other ML primitives.
• Collaborate with ML engineers to identify performance bottlenecks in training and inference pipelines.
• Develop benchmarks and regression tests to safeguard performance over time.
• Evaluate new GPU architectures and featuresets, and advise on adoption strategy.
• Contribute to compiler-level optimizations for tensor programs where appropriate.

Skills

CUDA programming

GPU performance engineering

C++

Profiling

HPC architectures

ML frameworks integration

Education

Bachelor’s or Master’s degree in CS/CE

Tools

NCCL

MPI

Nsight Systems

Nsight Compute

CUDA profilers

Triton

Job description

Bright Vision Technologies is seeking a GPU Systems Engineer to design and optimize compute-intensive workloads on modern accelerator hardware. You will deliver high-performance CUDA kernels, profile using Nsight tools, and collaborate with cross-functional teams to translate requirements into engineered solutions.

The role focuses on AI training, inference, scientific computing, and high-throughput data processing, with a strong emphasis on performance, reproducibility, and scalable