Modal jobs, judged for you, free

What they do

Modal builds cloud infrastructure for AI. Customers get GPUs, the chips that run AI models, when they need them, and containers (packaged programs) that start in under a second. They use it to run AI models, train models further, and run code in sealed-off sandboxes. Modal built its own file system, container runtime, and scheduler. Pricing is by usage.

What they value

• Put developer experience, how easy the product is for programmers, at the core.
• Go deep and build the infrastructure yourself to deliver that experience.
• Put the customer first: customer, then company, then team, then me.
• Work with high influence and low ego, and share credit freely.
• Take ownership and drive work to completion.

Where they hire

The 39 Postings name four offices: New York (31), San Francisco (21), Stockholm (9), and London (6). Many roles name more than one office. Many Postings ask for in-person work, and the enterprise sales role says five days a week. Two roles are marked remote or hybrid. No Posting mentions visa sponsorship.

Teams and roles

Engineering has 25 of the 39 Postings. The go-to-market (GTM) and general and administrative (G&A) groups have 6 each.

• Systems and platform: Member of Technical Staff roles in systems, storage, machines, platform engineering, the Python SDK (software development kit), product, and machine learning (ML) performance, plus systems engineering managers.
• Research: researchers in inference (running trained models) and post-training (improving a model after its first training), and a PhD ML research intern.
• Forward Deployed Engineers, in ML and in systems, work on customer workloads. Customer Engineers split their time between customers and platform code.
• Security: infrastructure security engineers, and detection and response engineers.
• Sales: an enterprise account executive, an account manager, a regional director, a solutions architect, and revenue operations.
• Also a documentation engineer, a developer relations engineer, a brand designer, an analytics engineer, and people and business operations roles.

What they look for

Systems and storage roles ask for 5+ years of production code and of large distributed systems, which run across many machines. They also ask for deep knowledge of Linux internals (the kernel, file systems, containers) and performance work. Rust is a plus. Several engineering roles join an on-call rotation and respond to production incidents. ML roles ask for inference, training, or GPU work, and depth in a model-serving tool such as vLLM or SGLang. Forward Deployed and customer roles ask for clear communication with engineers and executives. Systems Forward Deployed Engineers also need a major cloud (AWS, GCP, or Azure) and the container tools Docker and Kubernetes. The enterprise account executive needs 7 to 10+ years of enterprise sales and sales targets (quotas) of $1M or more. Forward Deployed Engineer Postings count open-source work and side projects as a bonus.