# People Operations Generalist at Modal > Onsite · United States · Unspecified · Other · open. Source: https://alderhq.app/jobs/ashby%3Amodal%3A17eba4cc-3a50-4f6e-b55b-bf20180091f2 (read 2026-11-14). ## Facts (observed) - Company: [Modal](https://alderhq.app/companies/modal) - Location text: New York - Where it can be done from (inferred): Onsite · United States (evidence: "Location: New York") - Posted: 2026-06-17 (150 days ago) - First seen by alder: 2026-11-02 · last verified: 2026-11-09 - Reposted: 0 times · edited: 0 times - Apply on the employer's site: https://jobs.ashbyhq.com/modal/17eba4cc-3a50-4f6e-b55b-bf20180091f2 - Skills listed (inferred): Docker ## Pay and sponsorship - Posted pay: $115k–$145k per year (from the listing's pay field) - Market band for similar posted roles (New York, n 4127): p25 $60k, median $99k, p75 $162k - H-1B filings at this company for similar roles, FY26: 1 ([US DOL OFLC LCA disclosure data](https://www.dol.gov/agencies/eta/foreign-labor/performance)) ## Description (the employer's text) ### About Us 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 Ramp, 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've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. 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’re looking for a People Operations Generalist to join our growing People team. You’ll touch the employee lifecycle end-to-end, from offer acceptance through offboarding, while helping to build the processes and documentation that let our People function scale with the business. This is a great fit for a highly organized, systems-oriented people person who thrives in a fast-paced environment and wants to build operational foundations, not just maintain them. ### What You’ll Work On Own and continuously improve the new hire onboarding experience, ensuring employees are set up for success and internal tasks are tracked and completed on time Serve as a first point of contact for employee questions across the full HR spectrum, triaging and routing more complex issues to the right People team member or external partner Maintain and improve self-service resources (FAQs, Notion pages, etc.) so employees can find what they need quickly and always feel supported, even when no one’s in the room Support rollouts of new People programs and policies, including communication planning, manager enablement, and documentation Help bring employee experience programs and events to life that reinforce culture and make people feel valued, from team offsites to milestone recognition Process employee changes (promotions, equity refreshes) accurately and on time, including preparing updated employment letters and maintaining compliant employee files ### You May Be a Fit If You have 2+ years of People Operations experience, preferably at a high-growth startup You’ve built and documented HR processes from the ground up, not just executed existing ones You have strong written communication skills: you write clearly, keep things simple, and know your audience You’ve managed employee data with accuracy and discretion You’re comfortable handling competing priorities without losing track of the details --- Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3Amodal%3A17eba4cc-3a50-4f6e-b55b-bf20180091f2 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.