About Huzzle Labs
Huzzle Labs builds RL environments for code, tool-use and computer-use alongside expert trajectories for frontier AI labs. We work with leading labs helping them close critical capability gaps through high-quality reinforcement learning environments and RLHF data.
Huzzle is one of the fastest-growing companies in the UK (ranked #7 by Sifted), with hubs in London, Berlin, and San Francisco.
The Role
This is a founding GTM hire for our Labs business. You will own the full sales cycle with frontier AI labs — from identifying capability gaps, to scoping RL environment solutions, to closing and delivering. This is not a traditional sales role. You need to deeply understand the technical landscape of RLHF, reinforcement learning, and AI research landscape to be a credible partner to research and engineering teams at the world’s leading AI labs.
What You’ll Do
- Build and own relationships with frontier AI labs (data operations, research, procurement)
- Identify capability gaps in model training and agent development through deep technical discovery
- Scope and sell custom RL environments and expert trajectory data to close those gaps
- Drive the full sales cycle from outbound through close, including pricing and contract negotiation
- Serve as the primary commercial interface between Huzzle Labs and its lab partners
- Feed insights from lab conversations back into product and delivery to keep our offering sharp
- Help shape GTM strategy, pricing, and positioning as the first dedicated hire in this function
What We’re Looking For
- Proven GTM experience selling to AI labs: human data, RLHF, RL environments, or adjacent infrastructure
- Ideally previously at companies like Scale AI, Mercor, Micro1, Surge AI, or similar
- Strong understanding of the frontier AI landscape: who’s building what, where the capability gaps are, and what labs actually need
- Ability to have technical conversations with ML engineers and researchers
- Comfort operating in ambiguity — this is a founding role with significant ownership and minimal structure
- Bias to action, low ego
- Based in San Francisco preferred; open to strong remote candidates across the US
Compensation
- Base salary: $170,000 – $210,000
- Meaningful early-stage equity
- Performance-based commission & bonus
