Specific Labs — Founding Strategic Projects Lead

Type: Full-time | On-site | San Francisco, CA Compensation: $120,000–$200,000 base + 5% commission on project margin (uncapped) + 0.5%–1.5% founding-tier equity Hiring count: 1 Visa sponsorship: None available Reports to: Sid (Co-Founder, delivery; ex-Intel AI research) — no LinkedIn provided

Specific Labs (formerly Bear) provides voice data and enterprise data to frontier AI labs. The voice side runs a network across 15 countries with the highest-quality data in Japanese and Arabic; the enterprise side partners with products and buys company data to build rich, real-world RL environments rather than synthetic ones.

YC-backed, $4M raised, $80K MRR (~$1M ARR annualized), working with top voice labs and frontier labs. Founders are Janak (ex-Coinbase; built a product that was acquired) and Sid (AI research at Intel). The team today is the two co-founders plus an active first engineering hire — this is the first operations hire.

Founded: 2025 | Team size: 1–10 (Seed) | Total funding: $4M Industry: AI Tools / AI data Website: withspecific.com Office: San Francisco, CA

• Founding-tier ownership: First operations hire — you represent ~30% of the company on day one and shape the culture directly.
• Fast trajectory: Clear path to Senior SPL or GM if delivery goes well.
• Uncapped upside: 5% commission on project margin (uncapped) plus 0.5–1.5% founding equity, on top of a $120–200K base.
• Real traction: YC-backed with live revenue (~$1M ARR) and frontier-lab customers.
• Genuinely creative work: Sourcing rare-language audio and novel data through unconventional channels — not running a standard marketplace.

Reconstructed from intake-derived notes in the posting — the intake video itself was not transcribable. Confirm with David before relying on these as verbatim intake points.

• First operations hire; the new hire represents ~30% of the company and contributes to culture from day one.
• Janak (co-founder) direct: candidates building ops from scratch need at least some grounding in human data delivery — prior human-data experience is a genuine must, not a nice-to-have.
• The candidate who previously fell through was a statistics major with consulting experience and data work — that profile is the target.
• Mercor alumni are a strong target pool; Mercor candidates often want out and Specific Labs is positioned as a direct culture upgrade.
• Commission economics: 5% margin per project, tied directly to delivery quality and speed — frame uncapped upside for strong delivery.
• Hard logistics: SF in-person 5.5 days/week; relocation supported from NY or LA; no visa sponsorship.
• The take-home is the real signal: given a budget, source ~1–2 hours of rare-language audio + transcription. Tests creativity and execution.

Specific Labs is hiring its first Strategic Projects Lead to own delivery for frontier-lab projects end-to-end — working directly with labs, managing contributors, building delivery ops from the ground up, and sourcing rare data through creative channels when standard playbooks won't work.

• →Deliver multiple datasets to frontier AI labs end-to-end (source, qualify, manage contributors, ship).
• →Build delivery ops from scratch: processes, contributor management, quality control.
• →Get creative on hard sources: rare languages, niche audio (people talking to AI agents), regulated data.
• →Leverage and grow Specific Labs' contributor network and partner products.
• →Manage commission economics: 5% margin on each project, directly tied to delivery quality and speed.

Tech stack: N/A — operations / delivery role; no specified engineering stack.

• 0-5 years, high slope, some human data experience
• Detail-oriented, ops-from-zero executor
• Creative sourcing: rare languages, niche audio
• $120-200K base + 5% commission uncapped
• 5.5 days a week, SF in-person
• Relocation supported from NY or LA

• Prior experience at a human data company (Mercor especially, plus Surge, Scale, Turing, Micro1, Scalar AI Labs). Mercor candidates often want out and Specific Labs is a direct upgrade on culture.
• Statistics, data science, or technical major. The candidate who fell through was a statistics major with consulting experience and data work.
• Creative sourcing track record: has personally built unconventional pipelines (Facebook group recruiting, partner negotiation, niche language networks).
• Equity-first mindset
• Personable and fun.

• Too senior
• Dishonesty or any history of being dishonest in a prior role
• Money-first motivation over building / equity.
• Cannot source creatively. Anyone who needs a defined playbook to operate will not deliver in this role.
• Not willing to be in SF in-person 5.5 days a week (or relocate from NY/LA).

Salary$120,000–$200,000 baseCommission5% on project margin (uncapped)Equity0.5%–1.5% (founding-tier)On-site policySF in-person, 5.5 days/week; relocation supported from NY or LAVisa sponsorshipNone availableEmployment typeFull-timeLocationSan Francisco, CA

Note: the Job Details card listed equity as 0%–1%; the compensation line listed 0.5%–1.5% founding-tier. Using 0.5%–1.5% — confirm with David.

Benefits & perks: $120–200K base + 5% commission on margin (uncapped) + 0.5–1.5% founding-tier equity · DoorDash meal stipend · gym in building · health insurance.

None provided on the role page. Confirm with David whether any screening questions apply before the screening call.

Stage 1 — Pending Approval — Candidates awaiting initial approval. Stage 2 — Initial Screen Stage 3 — Take-Home Assignment (~3 days) — Given a budget, source ~1–2 hours of rare-language audio + transcription. Tests creativity and execution. Stage 4 — Culture-Fit Chat Stage 5 — On-Site Day in SF Stage 6 — Offer Extended Stage 7 — Candidate Hired — Candidate accepts and starts.

Updated June 24, 2026 Human data companies — Mercor (especially), Surge, Scale, Turing, Micro1, Scalar AI Labs, AfterQuery Adjacent backgrounds — Statistics / data science / technical PM; consulting or IB with operations/founding interest; multilingual or strong cross-cultural networks

For reference only — do not source these specific profiles. None with LinkedIn links provided on the role page.

• A prior candidate fell through; profile was a statistics major with consulting experience and data work (cited as the desirable profile type, not as a rejection reason). No detailed rejection feedback was provided on the page.