Performance Engineer, Deep Learning and HPC

at Nvidia

USD 116,000-212,800 per year

MIDDLE

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AWS @ 3 Automated Testing Azure @ 3 CentOS @ 6 Communication @ 3 Data Analysis @ 6 Debugging @ 5 Deep Learning @ 3 Docker @ 2 GCP @ 3 GPU @ 3 HPC @ 3 Linux @ 6 Machine Learning Marketing Performance Analysis PyTorch @ 3 Python @ 3 TensorRT @ 3

Details

NVIDIA is seeking a Performance Engineer focused on Deep Learning (DL) and High-Performance Computing (HPC) applications. The team generates benchmark data across a growing catalog of DL and HPC frameworks and applications on NVIDIA and competing products. This data supports sales and marketing materials as well as engineering studies for current and future products. The role involves automation, performance analysis, debugging, and collaboration with multifunctional teams across multiple active projects.

Responsibilities

Plan and execute performance benchmarking across a wide range of HPC and deep learning frameworks and applications.
Aggregate, analyze, and produce written and visual reports based on testing data for internal sales, marketing, software, and hardware teams.
Develop Python scripts to automate testing of DL- and HPC-focused applications.
Work with internal engineering teams to debug performance issues.
Learn and use the latest applications in advanced machine learning and HPC.
Assist with developing tools and processes that improve automated testing capabilities.

Requirements

Bachelor's 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 a scripting language such as Python or Unix shell.
Advanced knowledge of Linux-based systems; Ubuntu and CentOS are strongly preferred.
Proficiency compiling software from source code, including debugging compilation errors.
Excellent English verbal and written communication skills for collaboration with coworkers.
Strong data analysis skills and the ability to summarize findings in written reports.
Familiarity with a container platform such as Docker or Singularity.

Preferred Qualifications

Experience with GPU-enabled deep learning frameworks such as PyTorch, MXNet, or TensorRT.
Experience with GPU-enabled HPC applications such as LAMMPS, GROMACS, Amber, or RTM.
Experience with GPU/CPU benchmarking on cloud platforms including AWS, GCP, or Azure.
Experience with software compilers such as GNU, Intel Composer, or PGI.
Previous experience with computer clusters and cluster orchestration and scheduling tools.

Benefits

NVIDIA offers competitive salaries, equity, and a comprehensive benefits package.

The base salary range is USD 116,000–189,750 for Level 2 and USD 136,000–212,750 for Level 3. The base salary is determined by location, experience, and the pay of employees in similar positions. Applications will be accepted at least until October 9, 2026.