Remote GPU Systems Engineer for AI & HPC Optimization

Bright Vision Technologies; Plymouth (MN); Remote; USD 100,000 - 150,000; Full time

Job summary

Bright Vision Technologies in the United States is seeking a GPU Systems Engineer to design and optimize compute-intensive workloads on modern accelerator hardware. This role focuses on extracting maximum performance from GPU platforms for AI training, inference, scientific computing, and high-throughput data processing.

You will work with cross-functional teams to translate ambiguous requirements into well-engineered solutions, mentor junior engineers, and push the bar through code and design

Qualifications

• Bachelor’s or Master’s degree in CS/CE or related field.
• 6+ years of 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.
• Experience integrating custom kernels into ML frameworks.
• Strong C++ skills and systems programming.

Responsibilities

• Design and implement high-performance CUDA kernels for compute-intensive workloads across AI and HPC use cases.
• Profile and optimize GPU code using tools such as 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.
• Optimize multi-GPU and multi-node training using NCCL, RDMA, and high-performance networking.
• Implement custom operators and fused kernels in PyTorch, JAX, or Triton.
• 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, working at the boundary between ML frameworks and underlying accelerator code to unlock performance not reachable through framework-level tuning alone.
• Optimize memory hierarchy usage across HBM, L2, shared memory, and registers.
• Implement mixed-precision and quantized compute paths that maximize accelerator throughput while preserving numerical fidelity.
• Document performance characteristics, design decisions, and tuning playbooks for internal teams.
• Stay current with GPU architecture, CUDA evolution, and emerging accelerator technologies.

Skills

GPU performance engineering

CUDA programming

Cross-functional collaboration

Benchmarking and profiling

Education

Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related field

Tools

CUDA

Nsight Systems

Nsight Compute

NCCL

RDMA

PyTorch

JAX

Triton

CUTLASS

Job description

Bright Vision Technologies in the United States is seeking a GPU Systems Engineer to design and optimize compute-intensive workloads on modern accelerator hardware. This role focuses on extracting maximum performance from GPU platforms for AI training, inference, scientific computing, and high-throughput data processing.

You will work with cross-functional teams to translate ambiguous requirements into well-engineered solutions, mentor junior engineers, and push the bar through code and design