Talent Ops Manager

Job Title: Talent Ops Manager

Job Type: Full-time

Location: Remote

About Us:

micro1 is the end-to-end human data infrastructure behind AGI. Our AI recruiter model is used by frontier AI labs and Fortune 10s to source, vet, and deploy PhDs and professors from the world’s top universities at scale. These experts are placed directly into the training loops of the most advanced AI systems, powering the breakthroughs that move models forward. Our data platform converts their expertise into high-signal training datasets, and our talent management tooling measures, routes, and improves performance at scale.

Scope

Scale the human data engine behind frontier AI systems. Own onboarding, talent activation, and client success across high-velocity AI training deployments. Operate at the intersection of data, operators, and enterprise delivery.

What You’ll Own

1. Run large-cohort onboarding at scale (fast, clean, zero chaos).
2. Activate and manage distributed talent pools powering AI training + data ops.
3. Build and maintain high-trust enterprise client relationships.
4. Anticipate blockers before they surface — solve with speed and clarity.
5. Drive customer success outcomes across ongoing AI deployments.
6. Publish weekly performance + milestone reports (no noise, high signal).
7. Host community syncs / engagement rituals to keep operators sharp.
8. Partner with product + engineering to align talent ops with shifting model and client needs.
9. Continuously refine onboarding, QA, and retention systems using data.

What We're Looking For

1. Elite written communicator. Clear. Structured. Direct.
2. Proven operator in remote, distributed environments.
3. Deep ownership mindset — you don’t “manage,” you own.
4. Comfortable leading 100+ contributors without losing signal.
5. Thrives in ambiguity, velocity, and constant iteration.
6. Data-fluent — dashboards, KPIs, performance diagnostics.

Preferred

1. Experience in Human Data, RLHF, AI training pipelines.
2. Background working with enterprise AI or technical clients.
3. Built or scaled data ops / talent ops systems before.
4. Familiar with modern tooling (ATS, analytics, project ops, automation).