RL Environment Software Engineer

TalentPluto, Inc.; San Francisco (CA); Remote; USD 180,000 - 220,000; Full time

Job summary

TalentPluto, Inc. is seeking an RL Environment Software Engineer to design and build environments that simulate real-world workflows and the agents that operate them.

You will join a brand-new RL team with strong growth potential and work across research and engineering to shape the future of our environments. You will lead backend infrastructure for reliability, scale, and production-readiness while applying reinforcement learning expertise to create impactful, high-quality simulation

Qualifications

• Strong ML engineering background.
• Experience building systems from scratch.
• Proficient in Node.js, Python, and React/TS.
• Comfort in a fast-paced startup with high ownership.

Responsibilities

• Design and build high-quality RL environments that simulate real workflows end to end.
• Develop agents for tasks within those environments and iterate for production readiness.
• Collaborate with research to anticipate future environment needs.
• Own the backend and infrastructure layers for reliability and scalability.
• Help establish engineering standards for a growing RL team.

Skills

Machine learning

Node.js

Python

React/TypeScript

Kubernetes

Docker

Education

Bachelor's degree in CS or related field

Tools

Docker

Kubernetes

Job description

Location: Remote (United States)

Work Model: Remote

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