Skip to main content
Tallo logoTallo logo
Apply for this opportunity

This job application is on an outside website. Be sure to review the job posting there to verify it's the same.

Member of Technical Staff - ML Performance

Job

Modal Labs

San Francisco, CA (In Person)

Full-Time

Posted 6 weeks ago (Updated 2 weeks ago) • Actively hiring

Expires 7/19/2026

Review key factors to help you decide if the role fits your goals.
Pay Growth
?
out of 5
Not enough data
Not enough info to score pay or growth
Job Security
?
out of 5
Not enough data
Calculating job security score...
Total Score
79
out of 100
Average of individual scores

Were these scores useful?

Skill Insights

Compare your current skills to what this opportunity needs—we'll show you what you already have and what could strengthen your application.

Job Description

Member of Technical Staff - ML Performance Modal Labs Software Engineering, IT, Data Science San Francisco, CA, USA • New York, NY, USA Posted 6+ months ago Apply now
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! Details Work in-person, in our NYC, San Francisco or Stockholm office Full medical, dental, vision insurance Competitive salary and equity Requirements 5+ years of experience writing high-quality production code. Experience working with torch, huggingface libraries, modern inference engines (vLLM or TensorRT). Familiarity with Nvidia GPU architecture and CUDA. Familiarity with low-level operating system foundations (Linux kernel, file systems, containers, etc.) Experience with ML performance engineering (tell us a story of when you pushed GPU utilization higher!) Apply now See more open positions at Modal Labs