AI needs a new infrastructure layer. We're building it at Modal.
Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now.
Our customers include category-defining companies like Lovable https://modal.com/blog/lovable-case-study, Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale.
We recently raised a $355M Series C https://modal.com/blog/modal-series-c at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September.
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.
What you'll do
Modal is the cloud platform built for AI. We're used by the world's leading AI labs, startups, and researchers to run compute-intensive workloads: training runs, inference, sandboxed code execution, and more.
We need someone to own and grow our presence in academia and research. That means running our Modal for Academics program https://modal.com/academics: sponsoring courses and labs with compute credits, building relationships with professors and researchers at top institutions, and making Modal the default choice when someone needs GPUs for their next paper.
The right person has lived in this world. You know how grant cycles work, how labs are structured, and how the conference publishing process actually runs. You've also shown you can operate beyond the lab, whether that's organizing events, building community, or working across institutional boundaries.
Own and operate the Modal for Academics program end-to-end: handling inbound inquiries, overseeing grant decisions, onboarding, and follow-through.
Identify and pursue sponsorship opportunities with university courses, ML research labs, and academic conferences, with a bias toward work that's likely to be widely read and cited.
Build relationships with professors and researchers at top universities.
Partner with leading AI research labs on compute grants and collaborative programs.
Track outcomes: which grants produced papers, citations, talks, or downstream Modal adoption.
Represent Modal at academic conferences (NeurIPS, ICLR, ICML, and others) and research-adjacent events.
Develop outreach templates, program documentation, and supporting content to scale inbound interest.
Requirements
A PhD or research Master's from a strong program in ML/CS or with a large computational component. You know how grants work, how labs are structured, and how the conference process actually runs.
Evidence that you've operated beyond pure research: organizing a workshop, running a student group, working with a grants office, industry internships, or similar.
Strong written and verbal communication, including on technical matters. You'll be representing Modal to professors and researchers at top universities.
Good judgment about what's worth pursuing. Not every course sponsorship or lab partnership is equal.
Organized and self-directed. This role spans dozens of active relationships at any given time.
Comfortable working in-person in a fast-paced startup environment.
Nice to have
Experience as a conference organizer, area chair, workshop chair, or reviewer at a major ML conference.
Existing relationships with professors and researchers at top universities.