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Senior Software Engineer – GPU Communications and Networking
| Company | NVIDIA |
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| Location | Santa Clara, CA, USA |
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| Salary | $148000 – $287500 |
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| Type | Full-Time |
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| Degrees | Master’s, PhD |
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| Experience Level | Senior |
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Requirements
- M.S./Ph.D. degree in CS/CE or equivalent experience
- 5+ years of relevant experience
- Excellent C/C++ programming and debugging skills
- Strong experience with Linux
- Expert understanding of computer system architecture and operating systems
- Experience with parallel programming interfaces and communication runtimes
- Ability and flexibility to work and communicate effectively in a multi-national, multi-time-zone corporate environment
Responsibilities
- Design, implement and maintain highly-optimized communication runtimes for Deep Learning frameworks (e.g. NCCL for TensorFlow/Pytorch) and HPC programming interfaces (e.g. UCX for MPI/OpenSHMEM) on GPU clusters
- Participating in and contributing to parallel programming interface specifications like MPI/OpenSHMEM
- Design, implement and maintain system software that enables interactions among GPUs and interactions between GPUs and other system components
- Creating proof-of-concepts to evaluate and motivate extensions in programming models, new designs in runtimes and new features in hardware
Preferred Qualifications
- Deep understanding of technology and passionate about what you do
- Experience with CUDA programming and NVIDIA GPUs
- Knowledge of high-performance networks like InfiniBand, iWARP etc.
- Experience with HPC applications
- Experience with Deep Learning Frameworks such PyTorch, TensorFlow, etc.
- Strong collaborative and interpersonal skills, specifically a proven ability to effectively guide and influence within a dynamic matrix environment
