High-Performance Computing Engineer

Bright Vision Technologies • Overland Park, KS

22h • $130,000 - $150,000 • Remote

About The Position

Bright Vision Technologies is seeking a High Performance Computing Engineer to design and optimize compute-intensive workloads on modern accelerator hardware. The role focuses on extracting maximum performance from GPU platforms for AI training, inference, scientific computing, and high-throughput data processing. The engineer will work with product, design, engineering, operations, and business stakeholders to turn ambiguous requirements into well-engineered solutions. The role also involves contributing to code and design reviews and mentoring more junior engineers. The successful candidate is expected to bring strong engineering discipline, clear communication, and a record of delivering meaningful work that performs reliably 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.

Nice To Haves

• Experience with Triton, CUTLASS, or other GPU kernel authoring frameworks.
• Familiarity with TensorRT, FasterTransformer, or vLLM internals.
• Exposure to compiler infrastructure such as LLVM or MLIR.
• Open-source contributions to GPU or ML performance libraries.
• Experience with large-scale distributed training infrastructure.

Responsibilities

• Design and optimize compute-intensive workloads on modern accelerator hardware.
• Improve performance of GPU platforms used for AI training, inference, scientific computing, and high-throughput data processing.
• Profile and optimize GPU workloads in production.
• Integrate custom kernels into ML frameworks.
• Collaborate with product, design, engineering, operations, and business stakeholders to translate requirements into solutions.
• Participate in code and design reviews and mentor more junior engineers.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior