Hud — Customer Operations Lead

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

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://(Use the "Apply for this Job" box below).:
San Francisco, CA

• 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).

• 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.

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.

• 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 / escape); 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.).

• 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…