GPU Systems Engineer (CUDA)
Not Disclosed•Full-TimeRemote
location_on3155;3158, Cardenas Terrace, Centerville District, Fremont, Alameda County, California, 94536, United States
About the Team
Bright Vision Technologies is a forward-thinking software development company dedicated to building innovative solutions that help businesses automate and optimize their operations. We leverage cutting-edge technologies to create scalable, secure, and user-friendly applications. As we continue to grow, we are looking for skilled engineers to join our dynamic team and contribute to our mission of transforming business processes through technology.
About the Role
This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential. As a GPU Systems Engineer (CUDA), you will work directly as a full-time W2 employee of Bright Vision Technologies on our in-house Statement of Work (SOW) delivery roadmap. There is no third-party client, vendor, or implementation partner involved; you will be contributing directly to our internal deliverables.
In this role, you will partner with cross-functional teams—including product, design, engineering, operations, and business stakeholders—to translate ambiguous requirements into well-engineered solutions. You 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.
Hiring Process
For every role, a technical coding assessment is mandatory. Please apply only if you are confident in your technical abilities and hands-on experience. For immediate consideration, please send your resume to hilda@bvteck.com or contact us at (908) 698-4899. Learn more about Bright Vision Technologies at www.bvteck.com.
Equal Opportunity
Bright Vision Technologies is an Equal Opportunity Employer, including Disability/Veterans. We recognize that our people are our strength, and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company.
We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy, or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. BV Teck expressly prohibits any form of workplace harassment or discrimination.
Work location
Work model: Remote
3155;3158, Cardenas Terrace, Centerville District, Fremont, Alameda County, California, 94536, United States
Fremont, California
Key Responsibilities
- check_circleDesign and implement high-performance CUDA kernels for AI and HPC workloads
- check_circleProfile and optimize GPU code using Nsight Systems, Nsight Compute, and CUDA profilers
- check_circleTune memory access patterns, occupancy, register usage, and shared memory utilization
- check_circleDevelop highly optimized libraries for linear algebra, attention, and ML primitives
- check_circleOptimize multi-GPU and multi-node training using NCCL, RDMA, and high-performance networking
- check_circleImplement custom operators and fused kernels in PyTorch, JAX, or Triton
- check_circleCollaborate with ML engineers to identify performance bottlenecks in training and inference pipelines
- check_circleDevelop benchmarks and regression tests to safeguard performance over time
- check_circleEvaluate new GPU architectures and feature sets to advise on adoption strategy
Requirements
- verifiedBachelor's or Master's degree in Computer Science, Computer Engineering, or related field
- verified6+ years experience in GPU programming and performance engineering
- verifiedDeep expertise in CUDA C/C++
- verifiedStrong C++ skills
- verifiedFamiliarity with NCCL, MPI, and high-performance interconnect technologies
- verifiedExperience integrating custom kernels into ML frameworks
- verifiedSolid grounding in linear algebra and numerical methods
- verifiedNo new H1B sponsorship available; H1B transfers welcomed
- verifiedMandatory technical coding assessment
Nice to Have
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.
