Hud — Customer Operations Lead

Type: Full-time | On-site | San Francisco, CA (or Singapore) Compensation: $120,000–$150,000 + competitive equity Hiring count: 1 Visa sponsorship: None available — candidates must already hold work authorization for the US (or Singapore). Confirm work authorization in outreach / on the call. Reports to: Not specified on role page

About Hud

Hud is building the infrastructure to create reinforcement-learning (RL) training data and evaluations for frontier AI agents, plus a marketplace to sell them to frontier labs. The platform is already used by frontier labs, Fortune 500 companies, and startups. Hud was part of Y Combinator's W25 batch and has raised $16M (Series A led by Standard Capital, founded by a former YC partner).

Founded: 2024 | Team size: ~15 | Total funding: $16M (Series A) Industry: AI Tools / RL infrastructure Website: https://www.hud.ai/ Office: San Francisco, CA

Why Candidates Should Join

• Frontier-adjacent work: Sit at the human-in-the-loop layer between RL-data vendors and the frontier labs / enterprises buying from them — the implementation counterpart to Hud's GTM Engineers.
• Exceptional team: ~15 people including four International Olympiad medalists (IOI, ILO, IPhO), serial AI-startup founders, and ICLR/NeurIPS-published researchers; YC W25; eight figures raised and high revenue growth, scaling profitably.
• Real ownership, not a support seat: Deliberately not reactive — you turn recurring problems into processes, platform improvements, and lightweight systems, with competitive equity and full benefits (100% covered medical/dental/vision, meals in office, Equinox, 401k, unlimited AI tools).

Intake Call Summary

• No intake transcript is present in the pasted HTML. An Intake Video is posted on Contrario but its contents were not captured — recommend watching it before scoring and updating this section with the key points.

The Role

Own the customer-facing work at Hud that can't or shouldn't be automated — the human-in-the-loop layer across both sides of the marketplace: data suppliers (vendors) and frontier labs / enterprise buyers.

The work leans toward vendors (there are far more vendors than buyers) and toward education: many vendors are non-technical (e.g. a small accounting shop new to AI), so much of the job is patiently explaining what Hud does and how the platform, bidding, and project process work. This is deliberately not a customer-service role and not a closing role; unlike the GTM Engineers, it does not require prior RL knowledge. It is not purely reactive — you're expected to turn recurring issues into better processes and systems over time. May also run some demos.

What You'll Be Doing

• Own the human-in-the-loop layer of Hud's operations across vendors and buyers (frontier labs and enterprises)
• Jump into customer conversations when a human touch is needed to build trust, clarify context, or move things forward
• Resolve contract, onboarding, and platform blockers by working with the right internal owners
• Turn recurring customer issues, feedback, and learnings into better processes, platform, and communications
• Build lightweight systems that streamline workflows or make problems easier to resolve next time

Qualifications (from the role description, for sourcing detail):

• Must-have: customer/business ops, consulting, or similar background; sound judgment in customer-facing situations (help / push back / escalate); comfortable juggling many small-but-important threads; strong attention to detail and follow-through; has used AI tools to improve their own productivity.
• Nice-to-have: early-stage startup experience / works independently in fast-paced settings; experience with technical customers; familiarity with RL (environments, evals, benchmarks); thrives in unstructured problem spaces; ~1.5–2 years consulting followed by ~1 year at a startup (a strong entry-into-GTM path).

Tech stack: N/A — ops/GTM role; heavy daily use of AI tools (ChatGPT, Claude Code, Cursor, etc.).

Requirements

• Customer / business ops or consulting background
• Sound judgement in customer-facing situations
• Juggles many threads, high follow-through
• Uses AI tools in daily work
• On-site SF Bay Area or Singapore

Green Flags

• Sharp generalist with strong judgement about when to help, push back, or escalate
• Warm, patient communicator who can educate non-technical vendors without condescension
• Naturally juggles many small threads and follows through on all of them
• Already uses AI tools to work faster, and proactively turns recurring issues into process or automation improvements
• Consulting-plus-startup background looking to break into GTM, and can clearly explain what HUD does

Red Flags

• Reads as a traditional call-center / pure customer-service profile
• Needs heavy structure and explicit instructions; cannot operate as a generalist
• Wants a closing/quota GTM role, or expects to be a technical GTM engineer
• Cannot articulate what HUD does or shows no real interest in the space
• Unable to be on-site in the SF Bay Area or Singapore

Role Details

• Salary — $120,000–$150,000
• Equity — Competitive equity
• Experience — 0–5 years
• On-site policy — On-site; SF Bay Area or Singapore
• Visa sponsorship — None available. Candidates must already hold work authorization for the US (or Singapore). Not a candidate penalty, but requires a work-authorization question in outreach / on the call.
• Employment type — Full-time
• Location — San Francisco, CA (Singapore also acceptable per Requirements)

Screening Questions

(Contrario "Required Candidate Q&A" — asked on the Contrario submission form; the substantive ones inform the call and the Additional Notes.)

1. LinkedIn Profile
2. GitHub URL
3. Publications (e.g. Google Scholar) URL
4. Website
5. Why are you interested in working at Hud? (can be short)
6. What is the most difficult thing you've worked on, or done? Why?
7. Location
8. Are you open to relocation for this role?
9. Do you require visa sponsorship to take this role?
10. When is the earliest you would want to start working with us?
11. Do you have any deadlines or timeline considerations we should be aware of?
12. Additional Information

Interview Process

Stage 1 — Application Review — Contrario submission reviewed / approved. Stage 2 — First Round: Initial Screen — Initial screening conversation. Stage 3 — Second Round: Take-Home — Take-home exercise. Stage 4 — Third Round: Work Trial — Work trial. Stage 5 — Offer Extended Stage 6 — Candidate Hired — Candidate accepts and starts.