AI Systems Intern - Supercomputing & Hardware Co-Design

Etched; San Jose (CA); On-site; USD 34,440 - 55,104; Full time

Benefits offered by this job

Generous housing support for those relocating

Daily lunch and dinner in the office

Direct mentorship from industry leaders

Job summary

A cutting-edge AI technology company in San Jose is seeking interns for a supercomputing role focused on developing ML system software for rack-scale systems. Candidates should be pursuing or have a degree in Computer Science or Engineering and be proficient in C/C++ or Rust and Python. This paid 12-week internship offers generous housing support and direct mentorship from industry leaders. It provides an opportunity to tackle significant challenges in AI infrastructure.

Qualifications

• Experience with Linux internals, kernel development, or driver debugging.
• Experience with hardware diagnostics or interpreting hardware logs.
• Exposure to server virtualization or CI/CD pipelines.
• Experience with Rust or embedded development.

Responsibilities

• Design, develop, and deploy ML system software for operating rack-scale systems.
• Handle network performance, telemetry creation, and processing pipelines.
• Ensure secure and performant systems for data center scale ML workloads.

Skills

Proficiency in C/C++ or Rust

Proficiency in Python

Strong fundamentals in data structures and algorithms

Strong understanding of low-level software engineering

Excellent communication and collaboration skills

Education

Progress towards a Bachelor’s, Master’s, or PhD degree in Computer Science, Engineering, or a related technical field

Job description

A cutting-edge AI technology company in San Jose is seeking interns for a supercomputing role focused on developing ML system software for rack-scale systems. Candidates should be pursuing or have a degree in Computer Science or Engineering and be proficient in C/C++ or Rust and Python. This paid 12-week internship offers generous housing support and direct mentorship from industry leaders. It provides an opportunity to tackle significant challenges in AI infrastructure.