Parallel Computing Engineer
视技术是一家提供云，人工智能，数据和企业解决方案的科技咨询和软件开发公司。这是一个非常好的机会加入一家既定且受尊敬的组织，提供巨大的职业增长潜力。工作称号平行计算工程师位置：100%远程 （美国）职位类型：全日制，直接 W2工资范围：130,000~180,000美元年经验要求：10+年的赞助：美国公民，绿卡持有人，EAD 持有人和 H-1B 转让候选人鼓励申请。我们无法赞助新的 H-1B 签证申请本职位简介。光视觉技术正在寻找一个经验丰富的并行计算工程师，拥有10年以上高性能计算 (HPC),GPU 编程和平行计算方面的经验，以优化 AI,机器学习和科学计算工作负载。理想候选人将拥有 CUDA,GPU 架构，分布式计算，绩效优化和大规模人工智能基础设施的深入专业知识，具有企业和研究环境设计高性能计算解决方案的证明记录。关键责任 ·为 AI,深度学习和科学计算机应用程序设计，开发和优化高性能 CUDA 核。·利用 NVIDIA Nsight Systems,Nsight Compute,CUDA Profiler 以及相关性能分析工具来分析，配置和优化 GPU 工作负载。·优化 Gpu 内存管理，核执行，多 GPU 扩展和分布式计算性能。·设计可扩展的分布式培训和推断架构使用 NCCL,MPI,CUDA 知情通信库和高性能网络技术。·开发自定义 GPU 操作员和针对 PyTorch,JAX,Triton, TensorFlow 或类似 AI 框架的优化的内核。·提高大型语言模型 (LLM),深度学习和高性能人工智能工作负载的培训和演示性能。·与人工智能研究人员，ML 工程师和软件架构师合作以加速生产人工智能应用。·建立自动基准框架，性能回归测试和优化管道。·评估新兴 GPU 技术，编程模型和加快器架构以提高计算效率。·指导工程师并提供 GPU 优化，HPC 架构和平行编程最佳实践的技术领导力。
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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: $130,000–$180,000 Annually
Experience Required:10+ 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 a highly experienced Parallel Computing Engineer with 10+ years of experience in High-Performance Computing (HPC), GPU programming, and parallel computing to optimize AI, machine learning, and scientific computing workloads. The ideal candidate will possess deep expertise in CUDA, GPU architecture, distributed computing, performance optimization, and large-scale AI infrastructure, with a proven track record of designing high-performance computing solutions for enterprise and research environments.
Key Responsibilities
- Design, develop, and optimize high-performance CUDA kernels for AI, deep learning, and scientific computing applications.
- Analyze, profile, and optimize GPU workloads using NVIDIA Nsight Systems, Nsight Compute, CUDA Profiler, and related performance analysis tools.
- Optimize GPU memory management, kernel execution, multi-GPU scaling, and distributed computing performance.
- Design scalable distributed training and inference architectures using NCCL, MPI, CUDA-aware communication libraries, and high-performance networking technologies.
- Develop custom GPU operators and optimized kernels for PyTorch, JAX, Triton, TensorFlow, or similar AI frameworks.
- Improve training and inference performance for large language models (LLMs), deep learning, and high-performance AI workloads.
- Collaborate with AI researchers, ML engineers, and software architects to accelerate production AI applications.
- Build automated benchmarking frameworks, performance regression testing, and optimization pipelines.
- Evaluate emerging GPU technologies, programming models, and accelerator architectures to improve computational efficiency.
- Mentor engineers and provide technical leadership in GPU optimization, HPC architecture, and parallel programming best practices.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical discipline.
- 10+ years of professional experience in GPU programming, High-Performance Computing (HPC), or parallel computing.
- Expert-level proficiency in CUDA C/C++, GPU architecture, and massively parallel programming techniques.
- Extensive experience with NCCL, MPI, CUDA-aware MPI, and distributed GPU communication frameworks.
- Strong understanding of GPU memory hierarchy, kernel optimization, occupancy tuning, and performance analysis.
- Hands-on experience integrating custom GPU kernels into PyTorch, TensorFlow, JAX, Triton, or other machine learning frameworks.
- Strong C/C++ programming skills with expertise in debugging, profiling, and performance optimization.
- Experience developing scalable AI or HPC solutions on cloud platforms or large GPU clusters.
- Excellent analytical, communication, collaboration, and technical leadership skills.
Preferred Qualifications
- Experience with Triton, CUTLASS, TensorRT, FasterTransformer, vLLM, DeepSpeed, or similar GPU optimization frameworks.
- Knowledge of LLVM, MLIR, compiler optimization techniques, or code generation technologies.
- Experience with large-scale distributed AI training, model parallelism, pipeline parallelism, and inference optimization.
- Familiarity with cloud-based GPU infrastructure on AWS, Microsoft Azure, or Google Cloud Platform (GCP).
- Contributions to open-source GPU libraries, research publications, patents, or technical presentations.
- Experience with emerging accelerator technologies such as AMD ROCm, Intel
How to Apply
Would you like to know more about this opportunity? For immediate consideration, please send your resume to or contact us at (908) 505-3545. Learn more about Bright Vision Technologies at .
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.
Originally posted on Himalayas