Member of Technical Staff - Cloud Substrate

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 high 8-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:

At Modal, we dynamically scale workloads across many cloud providers (see Linear Programming for Fun and Profit). We are looking for engineers with backgrounds spanning cloud infra, data engineering, and mathematical optimization to push this system to the next level.

This role is for people who are deep systems thinkers and love optimizing things. You will be responsible for the system end-to-end, including things like:

• Negotiating with cloud vendors and influencing our cloud strategy.

• Modeling GPU and resource costs.

• Coming up with, backtesting, and rolling out new optimizations.

• Designing the next iteration of our workload scheduling system.

• Pricing new product offerings and GPU types.

Requirements:

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

• Strong cloud skills, and deep familiarity with at least one of AWS, GCP, Azure, Oracle Cloud.

• Experience with data science, visualization, and statistics.

• A love for optimizing stuff, especially the bottom line.

• Familiarity with linear programming solvers and related optimization techniques is a plus.

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