Senior GPU Applications Engineer - Remote

Bright Vision Technologies; Orlando (FL); Remote; USD 100,000 - 150,000; Full time

Job summary

Bright Vision Technologies is seeking a GPU Applications Engineer to design and optimize compute-intensive workloads on modern accelerator hardware, focusing on CUDA programming, GPU architecture, and high-performance computing for AI training and HPC workloads. This role emphasizes delivering measurable performance improvements across production GPU systems.

You will collaborate with cross-functional teams to translate ambiguous requirements into production-ready solutions, mentor junior

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.
• Understanding of modern GPU architectures, memory hierarchies, and execution models.
• 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 modern systems programming practices.
• Solid grounding in linear algebra and numerical methods.
• Strong communication and collaboration skills with research and engineering teams.

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 feature sets, 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 codegen 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 within bounds acceptable for the target workloads.
• Document performance characteristics, design decisions, and tuning playbooks for internal teams.
• Stay current with GPU architecture, CUDA evolution, and emerging accelerator technologies.

Skills

CUDA/C++

GPU architecture

Performance profiling

NCCL

MPI

C++ programming

Education

Bachelor’s or Master’s in CS/CE

Tools

Nsight Systems

Nsight Compute

CUDA profilers

Triton

CUTLASS

TensorRT

Job description

Bright Vision Technologies is seeking a GPU Applications Engineer to design and optimize compute-intensive workloads on modern accelerator hardware, focusing on CUDA programming, GPU architecture, and high-performance computing for AI training and HPC workloads. This role emphasizes delivering measurable performance improvements across production GPU systems.

You will collaborate with cross-functional teams to translate ambiguous requirements into production-ready solutions, mentor junior