Founding Member of Technical Staff — RL

Naïve develops an AI platform for deploying autonomous employees that create, run, and automate software-driven businesses. The company provides autonomous company infrastructure and runtime environments that let users…

Location: Mountain View, CA
Company size: 1–10
Posted: 2w ago
Via: Yc

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Job listing · Updated 20 SEP 2026

Founding Member of Technical Staff — RL

Naive· Mountain View, CA, USView company profile

Job title: Founding Member of Technical Staff — RL
Job location: Mountain View, CA, US
Job listing URL: https://www.ycombinator.com/companies/naive/jobs/OTnFKjw-founding-member-of-technical-staff-rl
Job description: ## About Naive Naive is building autonomous companies: agent systems capable of operating real businesses end to end. We release autonomous company templates and benchmarks, alongside a studio—where users can deploy and operate these systems. Our infrastructure platform, Vetta, powers long-running, high-volume agent workloads. We’ve raised $28.5M from Nexus Venture Partners, Y Combinator, Zetta Venture Partners, Liquid 2 and leading operators. ## The Role Build real-world agent environments, benchmarks and autonomous company blueprints—and make Vetta the best-performing agent within them. Accordingly, as a founding MTS member, you have the chance to earn significant equity in a fast growing Series A company. ## What You’ll Do * Turn complex business workflows into reproducible agent environments * Design tasks, rewards, evals and benchmarks that measure real outcomes * Build production-ready autonomous company blueprints * Run experiments, analyze failures and improve agent performance * Develop training data and optimization loops from agent trajectories * Publish credible benchmarks, technical reports and demos ## Must-Haves * Strong Python and research-engineering ability * Experience building agents, evals or RL environments * Deep understanding of tool use, long-horizon tasks and LLM failure modes * Ability to design rigorous experiments and ship production systems * High agency and comfort working on ambiguous 0→1 problems ## Nice-to-Haves * RL or post-training experience * Browser, coding or computer-use agent experience * Experience publishing benchmarks or technical research * Familiarity with distributed agent infrastructure _P.S. If you’ve made it to the bottom of this listing and are serious about every point on this role, send Sean a LinkedIn connect with a note._

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