MO

Member of Technical Staff - Systems

Modal
Posted onFeb 16, 2026
LocationNew York, New York, United States (On-site)
Employment typeFull-time
Salary$150k – $270k Yearly

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. Companies like Suno, Lovable, and Substack rely on Modal to move from prototype to production without the burden of managing infrastructure.

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 at a $1.1B valuation. We have thousands of customers who rely on us for production AI workloads, including Lovable, Scale AI, Substack, and Suno.

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, 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 and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform.

Requirements:

  • 5+ years of experience writing high-quality production code

  • Experience building high-performance distributed systems at a large scale (the more battle scars, the better)

  • Strong cloud skills

  • Strong knowledge of low-level operating system foundations (Linux kernel, file systems, containers, etc.)

  • Experience with performance engineering (tell us a story of when you shaved off a few milliseconds!)

  • Ability to work in-person in our NYC office.

  • Prior experience with Rust is nice to have, but not required.

Salary: $150K – $270K • Offers Equity

Modal is a serverless compute platform for AI and data teams that enables running compute-intensive workloads like ML inference, fine-tuning, and batch jobs with instant GPU access and usage-based pricing.

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