# Founding Member of Technical Staff — RL

**Company:** [Naive](https://zerogtalent.com/ai-companies/naive)
**Location:** Mountain View, CA, US
**Work mode:** On-site
**Seniority:** Senior
**Employment type:** Full Time
**Salary:** USD 190K–225K/yr
**Category:** Research
**Listed:** 2026-09-19

[View and apply on Zero G Talent](https://zerogtalent.com/ai-jobs/naive/founding-member-of-technical-staff-rl-110962)

## What you'll do

- Turn complex business workflows into reproducible agent environments
- Design tasks, rewards, evals and benchmarks measuring real outcomes
- Build production-ready autonomous company blueprints
- Run experiments, analyze failures, improve agent performance
- Develop training data and optimization loops from agent trajectories

## What you need

- Strong Python and research-engineering ability
- Experience building agents, evals or RL environments
- Deep understanding of tool use, long-horizon tasks, LLM failure modes
- Ability to design rigorous experiments and ship production systems
- High agency and comfort with ambiguous 0→1 problems

## 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._

* * *

### Interview Process

### **About the interview**

1.  Screening call with Co-founder (CEO or CTO)
2.  Technical Interview (Project-based, no leetcode)
3.  Work trial offer / Full time conversion

## Other open roles at Naive

- [In-House Video Editor](https://zerogtalent.com/ai-jobs/naive/in-house-video-editor-115481) — Remote (US)
- [Growth Engineer Intern](https://zerogtalent.com/ai-jobs/naive/growth-engineer-intern-112022) — Mountain View, CA, US / Remote (US)
- [Founding Member of Techincal Staff - Agents](https://zerogtalent.com/ai-jobs/naive/founding-member-of-techincal-staff-agents-110963) — Mountain View, CA, US
- [Founding Product Engineer](https://zerogtalent.com/ai-jobs/naive/founding-product-engineer-110961) — Mountain View, CA, US
- [Founding Growth Engineer](https://zerogtalent.com/ai-jobs/naive/founding-growth-engineer-110960) — Mountain View, CA, US

---
*Source: [Zero G Talent](https://zerogtalent.com), the job board for space, defense, AI, robotics and frontier-tech companies.*