- Naïve
- Mountain View, CA
- Full-Time
- 16 days ago
Founding Member of Technical Staff — RL.
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Founding Member of Technical Staff — RL: our view in 3 lines...
- The Role:This role is for a research-engineering specialist building agent environments, benchmarks and autonomous company blueprints for AI systems.
- The Person:The person will turn business workflows into agent environments, design tasks rewards evals and benchmarks, build autonomous company blueprints, run experiments, improve agent performance, and publish benchmarks, technical reports and demos.
- Requirements:The ideal candidate has strong Python and research-engineering ability, experience building agents, evals or RL environments, and knowledge of tool use, long-horizon tasks and LLM failure modes.
About the role
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.
About the interview
- Screening call with Co-founder (CEO or CTO)
- Technical Interview (Project-based, no leetcode)
- Work trial offer / Full time conversion
Naïve is an autonomous company runtime.
You describe what your business does, and Naïve deploys AI employees that actually execute — building your app, closing deals, running campaigns, serving customers.
It works for new companies being built from zero and existing companies looking to automate entire functions by one-click connecting to your entire stack.
Deployed @ 500+ companies like Airwallex, Hackerrank, and more.