Member of Technical Staff - ML Training Systems
At a glance
Highlights
- Fast-growing AI infrastructure company
- Series B funded at $1.1B valuation
- Opportunity to contribute to open-source projects
Heads up
- On-call rotation required
- In-person work required in NYC or San Francisco
Why this role might suit you
The role suits engineers with strong ML training experience who enjoy building high‑performance infrastructure, contributing to open‑source, and working onsite with a fast‑growing AI platform team.
Skills
About the role
ABOUT US:
Modal provides the infrastructure foundation for AI teams. With instant GPU access, sub-second container startups, and native storage, Modal makes it simple to train models, run batch jobs, and serve low-latency inference. We have thousands of customers who rely on us for production AI workloads, including Lovable, Scale AI, Substack, and Suno.
We're a fast-growing team based out of NYC, SF, and Stockholm. We've hit 9-figure ARR and recently raised a Series B https://modal.com/blog/announcing-our-series-b at a $1.1B valuation. Our investors include Lux Capital https://www.luxcapital.com/, Redpoint Ventures https://www.redpoint.com/, Amplify Partners https://www.amplifypartners.com/, and Elad Gil https://eladgil.com/.
Working at Modal means joining one of the fastest-growing AI infrastructure organizations at an early stage, with many opportunities to grow within the company. Our team includes creators of popular open-source projects (e.g. Seaborn https://github.com/mwaskom/seaborn, Luigi https://github.com/spotify/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 training production machine learning models. If you are interested in contributing to open-source projects and evolving Modal's infrastructure to train the next generation of language models, we'd love to hear from you!
REQUIREMENTS:
- 5+ years of experience writing high-quality, high-performance code.
- Experience working with torch and high-level training frameworks (Huggingface, verl, slime)
- Experience with ML training optimization (tell us a story about eliminating data loading bottlenecks, overlapping communications with compute, rewriting a trainer to handle off-policy rollouts, 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 or San Francisco office.
- Ability to participate in on-call rotation and respond to production incidents.
Compensation
This Other role pays $150k-$350k/yr. Within typical range for other roles in United States.
Questions about this role
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