2027 Summer Intern, MS/PhD, AI-driven ML Performance Engineering Intern

Work with AI agents to create high performance low-level kernels in a Domain-Specific language for a custom ML accelerator

Ensure functional correctness and numerical accuracy of kernels

Conduct performance analysis of the kernels to identify performance bottlenecks and areas that need improvement

Develop a custom harness to recursively improve kernel generation and remove the need for human involvement

Currently enrolled in an MS or PhD program in Computer Science, Computer Engineering, Computational Science, or a related quantitative field

Demonstrated track record of using AI agents and harnesses to improve coding performance

Working knowledge of key kernels for transformer inference including performance analysis and optimization

Familiarity with one or more low-level ML accelerator DSLs (CUDA, Triton, Gluon, etc.)

Solid understanding of modern inference accelerator architectures

Fluency in Python and/or C++

Working knowledge of different ML numerical formats and their relative accuracy vs performance tradeoffs

Note: This will be a hybrid onsite internship position. We will accept resumes on a rolling basis until the role is filled. To be in consideration for multiple roles, you will need to apply to each one individually - please apply to the top 3 roles you are interested in.

The expected hourly rate for this full-time position is listed below. Interns are also eligible to participate in the Company’s generous benefits programs, subject to eligibility requirements.

Hourly Masters Pay

$70 — $70 USD

Hourly PhD Pay

$85 — $85 USD