About this 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. 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:
At Modal, we sell cloud services atop which our customers run their critical production systems. As a rapidly growing new cloud infrastructure company, we seek to improve our reliability dramatically while scaling the size of our platform and customer base.
This role is for people who are deep systems thinkers and love stacking nines. You would be the first reliability-focused hire at the company with the opportunity to define the company’s reliability systems and practices, and be a critical partner for our development teams.
Identify architectural changes to improve reliability, performance and availability.
Foster a culture of reliability across Modal’s engineering organization.
Design and implement key operational processes such as deployments, upgrades, rollbacks, and postmortem review.
Join a core engineering team and participate in on-call rotation, responding to production incidents.
Build monitoring systems that ensure the highest quality service for our customers.
Debug production issues across all services and levels of the stack.
Requirements:
5+ years of experience writing high-quality production code.
2+ years of on-call experience for critical production services.
Strong cloud skills, and deep familiarity with at least one hyperscaler cloud (AWS preferred).
Familiarity with auto scaling, fleet management, and capacity planning at scale.
Experience owning and scaling Kubernetes clusters to thousands of nodes a plus.
Experience with systems safety research (e.g. STAMP) and control theory a plus.
Ability to work in-person in our NYC office.
Other facts
About Modal
Deploy generative AI models, large-scale batch jobs, job queues, and more on Modal's platform. We help data science and machine learning teams accelerate development, reduce costs, and effortlessly scale workloads across thousands of CPUs and GPUs.
Our pay-per-use model ensures you're billed only for actual compute time, down to the CPU cycle. No more wasted resources or idle costs—just efficient, scalable computing power when you need it.
Deploy generative AI models, large-scale batch jobs, job queues, and more on Modal's platform. We help data science and machine learning teams accelerate development, reduce costs, and effortlessly scale workloads across thousands of CPUs and GPUs.
Our pay-per-use model ensures you're billed only for actual compute time, down to the CPU cycle. No more wasted resources or idle costs—just efficient, scalable computing power when you need it.
What you'll do
- The role involves improving the reliability of Modal's cloud services while scaling the platform and customer base. Responsibilities include identifying architectural changes, fostering a culture of reliability, and participating in on-call rotations.
Ready to join Modal?
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