Operations Manager - Supply

About Snorkel

Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes.

Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!

About the Role

Snorkel's expert network spans a growing set of specialized domains. Each one draws on a different talent pool, moves at a different speed, and carries its own bar for what a qualified expert looks like. Demand shifts between them as customer priorities change.

This role is the Supply DRI for one or more of those domains and the pods inside them, accountable for having the right experts, in the right numbers, allocated and productive when projects need them. Which domains you own will depend on where demand sits when you join, and will shift as the portfolio does.

The work is a mix of planning and execution. You own the middle of the funnel for the expert contributors (ECs) in your domain, from onboarding to project assignment. That includes building a staffing plan for every project in your domain, allocating ECs who are qualified for projects, maintaining a bench of vetted experts ahead of demand rather than sourcing after a request lands, and making allocation decisions that balance speed against quality of match.

Upstream, you’ll partner with our acquisition and recruiting team to grow supply for your domains. Downstream, you’ll work with Delivery to activate ECs on new projects, and with the Expert Experience team to keep our best experts engaged. You’ll be the Supply partner the pods come to, and you’ll also work closely with BPO partners and analytics.

Responsibilities

• Plan for now and next.
• Build a staffing plan for every project in your domains (role mix, peak targets, ramp timing and source mix), and flag gaps to Delivery before a project peaks. At the same time, keep a pre-vetted bench in each domain sized against forecast demand. Redeploy experts from ending projects before sourcing new ones.
• Make great matches.
• Allocate experts on credentials, domain fit and past performance, not just availability. Work with Delivery to learn what drives high-quality, high-acceptance work in each domain, and feed that back into how you vet and match.
• Own the results.
• You’ll be measured on: How many projects hit their staffing targets
• How fast supply arrives
• How many allocated experts get assigned to a project
• How quickly new experts find work
• When a number slips, find out why and fix it.
• Be the pods’ Supply partner.
• Act as the single point of contact for pod leadership, turn shifting priorities into supply moves, and escalate constraints early with options attached.
• Make it repeatable.
• Turn what you do into SOPs and help automate them, so the team scales with domains, not requests.

Requirements

• 4+ years in supply operations, workforce or staffing operations, marketplace operations, or a comparable role in a fast-moving environment.
• Experience sourcing, allocating, or managing a pool of specialized talent, and making trade-off calls when demand exceeds available supply.
• Comfort with data: you can pull your own numbers in SQL or a BI tool, and you have used a system of record (Airtable, Salesforce, or similar) as more than a place to log things.
• Experience building capacity plans or forecasts, including scenario planning when demand signals are uncertain.
• Track record of bringing structure to an ambiguous process: writing the SOP, getting people to follow it, and improving it once it runs.
• Strong cross-functional communication. You will spend much of your time aligning Delivery, recruiting, and external partners who each want something different.
• High ownership and a bias toward action, with the judgment to escalate the things that genuinely need a decision.
• Nice to have
• Experience working with credentialed or highly specialized professionals such as engineers, clinicians, researchers, or attorneys.
• Familiarity with credentialing, licensure verification, or handling regulated data.
• Experience with AI training data, annotation, or expert-in-the-loop work.
• Actual compensation will be determined based on factors including skills, qualifications, experience, and geographic location.