GPU Software Engineer (CUDA)

Bright Vision TechnologiesBright Vision Technologies·Remote(United States)
Software Development

WFA Digital Insight

The demand for skilled GPU software engineers has surged in recent years, with a 25% increase in job postings for CUDA specialists in 2025 alone. As companies like Bright Vision Technologies continue to push the boundaries of AI, HPC, and scientific computing, professionals with expertise in GPU architecture and high-performance computing are in high demand. With the remote job market booming, this role stands out for its competitive compensation package and opportunities for growth. Before applying, candidates should be prepared to showcase their technical prowess, particularly in CUDA programming and GPU optimization. With the right skills and experience, this role can be a launching pad for a successful career in the tech industry.

Job Description

About the Role

Bright Vision Technologies is a forward-thinking software development company that leverages cutting-edge technologies to create scalable, secure, and user-friendly applications. As a GPU Software Engineer, you will play a crucial role in designing and optimizing compute-intensive workloads on modern accelerator hardware. Your day-to-day responsibilities will involve collaborating with cross-functional teams to translate ambiguous requirements into well-engineered solutions.

The ideal candidate will have a strong engineering discipline, excellent communication skills, and a track record of delivering measurable performance improvements on production GPU systems. You will work closely with product, design, engineering, operations, and business stakeholders to raise the bar through code review, design review, and mentorship of junior engineers.

As a key member of the Bright Vision Technologies team, you will contribute to the company's mission of transforming business processes through technology. With a focus on innovation and growth, this role offers tremendous career growth potential for the right candidate.

What You Will Do

  • 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 cross-functional teams to translate ambiguous requirements into well-engineered solutions
  • Participate in code reviews, design reviews, and mentorship of junior engineers
  • Stay up-to-date with the latest developments in GPU architecture, CUDA, and high-performance computing

What We Are Looking For

  • 6+ years of experience in GPU software engineering, with a focus on CUDA programming and high-performance computing
  • Strong understanding of GPU architecture, memory hierarchy, and parallel computing concepts
  • Excellent programming skills in C++, Python, and CUDA
  • Experience with GPU profiling and optimization tools, such as Nsight Systems and Nsight Compute
  • Strong software engineering practices, including code review, design review, and testing
  • Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams
  • Experience with AI, HPC, or scientific computing applications, such as deep learning, linear algebra, or data processing
  • Strong problem-solving skills, with the ability to analyze complex problems and develop creative solutions

Nice to Have

  • Experience with other programming languages, such as Java, C#, or MATLAB
  • Familiarity with cloud-based GPU platforms, such as AWS or Google Cloud
  • Knowledge of containerization tools, such as Docker or Kubernetes
  • Experience with agile development methodologies, such as Scrum or Kanban
  • Certification in CUDA programming or GPU architecture

Benefits and Perks

  • Competitive base salary commensurate with experience
  • Comprehensive benefits package, including health, dental, and vision insurance
  • 401(k) matching program
  • Generous PTO policy, with paid holidays and vacation time
  • Remote work stipend, with options for home office setup and equipment reimbursement
  • Opportunities for professional growth and development, including training and conference attendance
  • Collaborative and dynamic work environment, with a team of experienced professionals

How to Stand Out

  • Develop a strong portfolio of your work, including examples of your CUDA programming and GPU optimization expertise.
  • Be prepared to discuss your experience with GPU architecture, memory hierarchy, and parallel computing concepts in detail.
  • Familiarize yourself with the latest developments in GPU technology and high-performance computing, including new tools and frameworks.
  • Practice your coding skills, particularly in C++, Python, and CUDA, to ensure you are prepared for technical interviews.
  • Research the company and the role thoroughly, including the company's mission, values, and culture, to demonstrate your interest and enthusiasm.
  • Be prepared to discuss your experience working with cross-functional teams and your ability to communicate complex technical concepts to non-technical stakeholders.

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