Posting record
Open 10+ days
- Talentpluto's site dates the posting
- Ghostless first sees this listing
- Last checked: still up
How we know
It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.
Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking Talentpluto, so its true age is longer.
Last checked Nov 1, 2026.
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Upload your resumeWhat it asks of you
- Bachelor's degree asked for
- Equivalent experience accepted instead of a degree
What the posting discloses
- Pay
- $180k to $220k a year USD
Compensation: $180K-$220K base, ~$400K+ OTE (uncapped profit share) (quoted from the posting)
Not stated: Real vacancy, AI screening.
Why these three
Ontario requires postings from employers with 25 or more staff to state the pay, whether the vacancy exists, and whether AI screens applicants.
Skills mentioned
About the role
Location: San Francisco, CA
Work Model: Onsite
Industry: Applied AI / AI research data
Compensation: $180K-$220K base, ~$400K+ OTE (uncapped profit share)
About the Company
Our partner is a fast-growing applied AI research lab that builds high-quality reinforcement-learning environments and agents sold to the world's leading AI labs. In under two years they have scaled to a nine-figure revenue run rate and grown their team severalfold in a matter of months, backed by leading venture investors. Quality is their core differentiator, and they are rapidly expanding into new domains.
The Opportunity
As an RL Environment Software Engineer, you will sit at the intersection of research engineering and traditional software engineering, building the environments that simulate real-world workflows and the agents that automate them. This is forward-looking work, you will help research and predict what high-quality environments the frontier will need next, then build them from the ground up.
You will join a brand-new RL team being assembled with exceptional talent, with a clear path to grow alongside it as the function scales into industry pods.
Responsibilities
- Design and build high-quality RL environments that simulate real working environments end to end.
- Develop agents for the tasks within those environments and iterate until they are efficient and production-ready.
- Partner with the research team to scope which environments to build and why, staying ahead of future demand rather than only meeting present needs.
- Own the backend and infrastructure layers that make environments reliable and scalable.
- Help set engineering standards for a zero-to-one team as the RL function grows.
Requirements
- Strong machine-learning engineers who code heavily and build systems from scratch, with strong intuition for reinforcement learning.
- Proficiency across a modern stack, Node.js and Python on the backend and React/TypeScript on the frontend, with strong Kubernetes and Docker skills.
- Comfort operating in a fast-paced startup environment with high ownership and long hours.
- A track record of meaningful tenure and impact at previous companies.
- Reinforcement-learning experience or an RL research background is a strong plus, though not required.
- Bachelor's degree in computer science or a related technical field, or equivalent practical experience.
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