2 days ago
Santa Clara, CA, USAMid Level
H1B sponsor
Base Salary
$116k - $213k/yr
Responsibilities
- Plan and execute performance benchmarking across Deep Learning and HPC frameworks, applications, and hardware.
- Aggregate and analyze testing data and generate written and visual reports for sales, marketing, software, and hardware teams.
- Develop Python scripts to automate testing of Deep Learning and HPC applications.
- Collaborate with internal engineering teams to debug performance issues.
- Learn and evaluate applications in advanced machine learning and HPC.
- Help develop tools and processes for automated testing.
Requirements
- Bachelor of Science degree in Computer Engineering, Computer Science, or a related technical field, or equivalent experience.
- At least 2 years of experience.
- Excellent programming and debugging skills in Python, Unix shell, or another scripting language.
- Advanced knowledge of Linux-based systems, with Ubuntu and CentOS strongly preferred.
- Proficiency compiling software from source code and debugging compilation errors.
- Strong English verbal and written communication skills.
- Strong data analysis skills and ability to summarize findings in written reports.
- Familiarity with a container platform such as Docker or Singularity.
- Preferred experience with GPU-enabled Deep Learning frameworks such as PyTorch, MXNet, or TensorRT.
- Preferred experience with GPU-enabled HPC applications such as LAMPS, GROMACS, Amber, or RTM.
- Preferred experience benchmarking GPUs and CPUs on AWS, GCP, or Azure.
- Preferred experience with GNU, Intel Composer, or PGI compilers.
- Preferred experience with computer clusters and cluster orchestration and scheduling tools.
Benefits
- Competitive salary, equity, and comprehensive benefits.
- Applications are accepted at least until October 9, 2026.
- This posting is for an existing vacancy.
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.