Staff RL Environments Engineer

Scale AI, Inc.; San Francisco (CA); On-site; USD 252,000 - 315,000; Full time

Benefits offered by this job

Health coverage

Dental coverage

Vision coverage

Retirement benefits

Learning stipend

Generous PTO

Commuter stipend

Job summary

Scale AI in San Francisco is seeking a Staff Software Engineer, RL Environments, to own the technical foundation for RL environments at scale, delivering reliable software for high-stakes AI workloads.

You will architect sandboxed execution, environment packaging and versioning, rollout orchestration, trajectory capture, and verifier frameworks, while creating authoring surfaces for engineers and domain experts.

Qualifications

• 8+ years of software engineering experience with fundamentals in distributed systems and algorithms.
• Strong Python skills and production software experience; familiarity with at least one other stack.
• Deep experience with containerization and sandboxed execution (Docker, VMs, Kubernetes, etc.).
• Experience building/high-throughput backend systems: orchestration, queuing, data pipelines.
• Hands-on experience with LLMs including agent loops, tool calling, and evaluation harnesses.
• Ability to own ambiguous problems end to end and ship a system.
• Excellent written and verbal communication; align engineers, researchers, and partners.

Responsibilities

• Own the technical foundation for RL environments at scale.
• Design platform: sandboxed execution, packaging/versioning, rollout orchestration, trajectory capture, verifier frameworks, and authoring surfaces.
• Instrument environments by mapping real apps and design task suites to reveal capability gaps and robust graders.
• Work across teams to set technical direction and write the hard parts.

Skills

Distributed systems

Python

Containerization

Other stack skills

Backend systems

LLMs / agent loops

Problem ownership

Communication

Tools

Docker

Kubernetes

VMs

gVisor/Firecracker

Job description

Scale AI in San Francisco is seeking a Staff Software Engineer, RL Environments, to own the technical foundation for RL environments at scale, delivering reliable software for high-stakes AI workloads.

You will architect sandboxed execution, environment packaging and versioning, rollout orchestration, trajectory capture, and verifier frameworks, while creating authoring surfaces for engineers and domain experts.