Performance Engineering Intern, Deep Learning

Job Description

Job Title: Performance Engineering Intern, Deep Learning and HPC - Winter 2026. Location: CA, US. Job Type: Internship (Full-time, Winter 2026)

You will work with cross-functional teams and gain hands-on experience in HPC systems, automation, and performance analysis.

Duties:

• Plan and execute GPU benchmarking for Deep Learning and HPC frameworks and applications.
• Collect, analyze, and present performance data through written and visual reports;
• Develop Python scripts to automate testing and benchmarking workflows.
• Debug and investigate performance issues in collaboration with engineering teams.
• Learn and evaluate modern Deep Learning and HPC applications;
• Support the creation of tools and processes that improve automated testing efficiency.
• Manage multiple tasks in a fast-changing and collaborative environment.

Qualifications:

• Currently pursuing a Bachelor’s degree in Computer Engineering, Computer Science, or a related field.
• Strong programming and debugging skills in Python or Unix shell;
• Advanced experience working with Linux systems such as Ubuntu or CentOS.
• Ability to compile software from source and resolve build issues.
• Strong data analysis skills and ability to summarize findings clearly.
• Good written and verbal English communication skills.
• Familiarity with container platforms like Docker or Singularity;
• Experience with Deep Learning frameworks such as PyTorch or TensorFlow is a plus.
• Exposure to GPU-enabled HPC applications, cloud benchmarking, or C++ development is a plus.

Benefits and Instructions:

• Internship duration: minimum 8 months (Winter 2026).
• Hourly pay range: $20 to $71 USD, based on location, education, and experience.
• Eligible for NVIDIA intern benefits;
• NVIDIA is an equal opportunity employer and values diversity and inclusion.
• To apply, upload your resume in English through the official application portal.