GPU Software Engineer (CUDA)

Bright Vision Technologies; United States; Remote; USD 80,000 - 107,000; Full time

Job summary

Bright Vision Technologies is seeking a GPU Software Engineer (CUDA) to design and optimize compute-heavy workloads on modern accelerators. You will push performance for AI training, inference, scientific computing, and data processing while collaborating with product, design, engineering, operations, and business stakeholders to translate vague requirements into solid, scalable solutions.

The role emphasizes mentorship, code and design reviews, and raising the bar for production-grade GPU

Qualifications

• Bachelor’s or Master’s degree in CS, CE, or related field.
• 7+ years of GPU programming and performance engineering.
• Deep CUDA C/C++ expertise and GPU programming models.
• Strong knowledge of modern GPU architectures and memory hierarchies.
• Experience profiling and optimizing production GPU workloads.
• Familiar with NCCL, MPI, and high‑performance interconnects.
• Experience integrating custom kernels into ML frameworks.
• Strong C++ skills and numerical methods background.
• Excellent communication and collaboration with teams.

Skills

CUDA

GPU programming

C++

Performance profiling

MPI/NCCL

Distributed training

Communication

Education

Bachelor's or Master’s degree

Tools

NCCL

MPI

CUDA Toolkit

LLVM/MLIR

Job description

GPU Software Engineer (CUDA)– Remote

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 fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.

Job Title

GPU Software Engineer (CUDA)

Location

100% Remote (U.S.)

Position Type

Full-time, Direct W2

Salary Range

$80,000–$107,000 Annually

Experience Required

7+ years

Sponsorship

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.

Job Summary

We are seeking a GPU Software Engineer (CUDA) 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.

Required Qualifications

• 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.

Bright Vision Technologies is an Equal Opportunity Employer.

Equal Employment Opportunity (EEO) Statement

Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall.

BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment.