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Naïve

Founding Member of Technical Staff — RL

Mountain View, CA, US · Not specified

Annual base salary
$190k – $225k USD
Equity
Not disclosed
Commitment
Full Time
Company stage
Not disclosed

Compensation as listed

$190K - $225K  •  2.00% - 4.00%

About Naïve

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.

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.

Technology

Python, Typescript, Docker, FastAPI, PostgreSQL, AWS, OpenAI

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

Source: Y Combinator. Confirm availability with the employer.

Apply through the original posting.

View listing