Member of Technical Staff - ML Performance

About Us:

At Modal, we build foundational technology, including an optimized container runtime, a GPU-aware scheduler, and a distributed file system.

We're a small team based out of New York, Stockholm and San Francisco, and have raised over $23M. Our team includes creators of popular open-source projects (e.g., Seaborn, Luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience.

The Role:

We are looking for strong engineers with experience in making ML systems performant at scale. If you are interested in contributing to open-source projects and Modal’s container runtime to push language and diffusion models towards higher throughput and lower latency, we’d love to hear from you!

Requirements:

• 5+ years of experience writing high-quality, high-performance code.

• Experience working with torch, high-level ML frameworks, and inference engines (vLLM or TensorRT).

• Familiarity with Nvidia GPU architecture and CUDA.

• Experience with ML performance engineering (tell us a story about boosting GPU performance — debugging SM occupancy issues, rewriting an algorithm to be compute-bound, eliminating host overhead, etc).

• Nice-to-have: familiarity with low-level operating system foundations (Linux kernel, file systems, containers, etc).

• Ability to work in-person, in our NYC, San Francisco or Stockholm office.