High-Performance Computing Engineer

Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. This is a full-time, direct W2 role with a salary range of $130,000–$150,000 annually.

About the role

We are seeking a High Performance Computing Engineer with deep expertise in CUDA programming, GPU architecture, and high-performance computing 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 workloads.

The ideal candidate combines low-level systems mastery with strong software engineering practices, and has a track record of delivering measurable performance improvements on production GPU systems. In this role you will work closely with cross-functional partners — product, design, engineering, operations, and business stakeholders — to translate ambiguous requirements into well-engineered solutions, and will be expected to raise the bar through code review, design review, and mentorship of more junior engineers. The successful candidate brings strong engineering discipline, a clear communication style, and a track record of shipping meaningful work that holds up well in production.

Responsibilities

• Design and optimize compute-intensive workloads on modern accelerator hardware
• Extract maximum performance from GPU platforms for AI training, inference, scientific computing, and high-throughput data processing
• Profile and optimize GPU workloads in production environments
• Integrate custom kernels into ML frameworks
• Collaborate with cross-functional teams to translate requirements into engineered solutions
• Participate in code reviews, design reviews, and mentorship of junior engineers

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

Preferred Qualifications

• 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

U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position.