Member of Technical Staff - Environments
About The Position
We’re looking for strong engineers - builders who can design and implement complex RL environments end-to-end. You’ll work at the intersection of research, systems engineering, and product, collaborating with infrastructure and research teams to create environments that test and steer model behavior at scale. You’ll be responsible for turning conceptual specifications into working environments with verifiable reward structures, automated verifiers, task generation pipelines, and reproducible simulations. These environments span from API- and web-based tasks to multi-agent simulations, structured reasoning challenges, and knowledge-work environments used by customers and researchers alike.
Requirements
- 3+ years experience in software engineering, simulation systems, or ML infrastructure
- Strong command of Python and systems-level programming
- Deep understanding of ML concepts. RL concepts are a plus - reward modeling, environment dynamics, verifiability, evaluation, and agent interaction loops
- Experience designing scalable data pipelines, browser or API simulations (e.g. Playwright, Selenium), or distributed compute frameworks
- Familiarity with instrumentation, metrics, and data pipelines for evaluation
- Proven ability to translate research or product goals into robust, maintainable systems
Responsibilities
- Design and implement RL environments that support large-scale agent evaluation and reinforcement learning experiments
- Build task generation pipelines, dynamic datasets, and scripted environments with controlled complexity and stochasticity
- Develop verifiers and reward models to automatically score trajectories and evaluate model reasoning
- Collaborate with infrastructure and systems engineers to ensure environments are scalable, reproducible, and instrumented for detailed telemetry
- Design APIs and orchestration frameworks for running, resetting, and evaluating agents across environments
- Partner with research and customer teams to translate open-ended specifications into verifiable, testable systems
- Optimize environment performance, logging, and reward reproducibility across distributed setups
Benefits
- Competitive salary and equity packages
- Health, dental, and vision insurance plans
- 401k plan
- Fun global offsites!
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
