Parallel Computing Engineer
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Parallel Computing Engineer
100,000–150,000 / Year
Location
Remote
Experience
Mid
Posted
Jul 30, 2026
Apply by
August 29, 2026
Applicants
0
Early applicantEasy applyFull-timeWork from Home
Job Description
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: Parallel Computing Engineer
Location: 100% Remote (U.S.)
Position Type: Full-time, Direct W2
Salary Range: $100,000–$150,000 Annually
Experience Required: 6+ 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
Bright Vision Technologies is seeking an experienced Parallel Computing Engineer with expertise in CUDA, GPU programming, and High-Performance Computing (HPC) to optimize AI, machine learning, and scientific computing workloads. The ideal candidate will have strong experience in GPU performance optimization, distributed computing, and modern ML frameworks.
### Key Responsibilities
- Design and optimize high-performance CUDA kernels for AI and HPC workloads.
- Profile and tune GPU applications using Nsight Systems, Nsight Compute, and CUDA tools.
- Optimize memory usage, multi-GPU performance, and distributed training with NCCL and MPI.
- Develop custom operators and optimized kernels for PyTorch, JAX, or Triton.
- Improve training and inference performance for large-scale ML workloads.
- Build benchmarks, automate performance testing, and document optimization best practices.
- Collaborate with ML and engineering teams to deliver scalable GPU solutions.
### Required Qualifications
- Bachelor's or Master's degree in Computer Science, Computer Engineering, or a related field.
- 6+ years of experience in GPU programming and performance optimization.
- Strong expertise in CUDA C/C++, GPU architectures, and parallel programming.
- Experience with NCCL, MPI, and high-performance networking.
- Hands-on experience integrating custom GPU kernels into ML frameworks.
- Strong C++ programming, debugging, and analytical skills.
### Preferred Qualifications
- Experience with Triton, CUTLASS, TensorRT, FasterTransformer, or vLLM.
- Knowledge of LLVM/MLIR or compiler technologies.
- Experience with large-scale distributed AI training and open-source GPU libraries.
How to Apply
Would you like to know more about this opportunity? For immediate consideration, please send your resume to [\[email protected\]](/cdn-cgi/l/email-protection) or contact us at (908) 505-3545. Learn more about Bright Vision Technologies at http://www.bvteck.com.
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.
Key Responsibilities
- Design and optimize high-performance CUDA kernels for AI and HPC workloads.
- Profile and tune GPU applications using Nsight Systems, Nsight Compute, and CUDA tools.
- Optimize memory usage, multi-GPU performance, and distributed training with NCCL and MPI.
- Develop custom operators and optimized kernels for PyTorch, JAX, or Triton.
- Improve training and inference performance for large-scale ML workloads.
- Build benchmarks, automate performance testing, and document optimization best practices.
- Collaborate with ML and engineering teams to deliver scalable GPU solutions.
Requirements
- Bachelor's or Master's degree in Computer Science
- Computer Engineering
- or a related field
Skills Required
CUDAGPU programmingHigh-Performance ComputingNCCLMPIC++PyTorchJAXTritonNsight SystemsNsight ComputeAnalytical skillsDebuggingCollaborationCUTLASSTensorRTFasterTransformervLLMLLVMMLIRCompiler technologiesDistributed AI trainingOpen-source GPU libraries
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