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Performance Engineering Intern – Deep Learning and HPC
| Company | NVIDIA |
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| Location | Santa Clara, CA, USA |
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| Salary | $18 – $71 |
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| Type | Internship |
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| Degrees | Bachelor’s, Master’s |
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| Experience Level | Internship |
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Requirements
- Pursuing Bachelors/MS in Computer Engineering, Computer Science or related technical field
- Excellent programming and debugging skills in a scripting language such as Python or Unix shell
- Advanced knowledge using Linux based systems (Ubuntu and CentOS strongly preferred)
- Proficient in compiling software from source code, including debugging errors encountered
- Excellent English verbal and written interpersonal skills to improve collaboration with coworkers
- Excellent data analysis skills and the ability to summarize findings in a written report
- Familiarity using a container platform such as Docker or Singularity
Responsibilities
- Plan and execute GPU performance benchmarking across a wide range of HPC and DL frameworks and applications
- Aggregate, analyze, and generate written and visual reports with the testing data for internal sales, marketing, SW, and HW teams
- Develop Python scripts to automate the testing of DL & HPC-focused applications
- Work with internal engineering team to debug performance issues
- Learn to use the latest applications in the fields of Deep Learning and HPC
- Assist with the development of tools and processes that improve our ability to perform automated testing
Preferred Qualifications
- Experience using a GPU-enabled deep learning framework such as TensorFlow, PyTorch, MXNet, or TensorRT
- Experience using GPU-enabled HPC applications such as LAMMPS, GROMACS, Amber, RTM, etc…
- Experience with GPU/CPU benchmarking on cloud solutions from AWS, GCP, Azure
- GPU programming experience in CUDA, OpenACC, or OpenCL
- Familiarity with software compilers such as GNU, Intel Composer, or PGI
