Requirements

Expected technologies

Python

Playwright

Selenium

Our requirements

• 5+ years of experience in software engineering, simulation systems, data science, or ML infrastructure.
• Strong command of Python and systems-level programming.
• Experience designing scalable task pipelines, browser or API simulations (e.g. Playwright, Selenium), or distributed compute frameworks.
• Understanding of RL concepts - reward modeling, environment dynamics, verifiability, evaluation, and agent interaction loops.
• Familiarity with instrumentation, metrics, and data pipelines for RL evaluation.
• Curiosity and conviction around building environments that steer AGI.

Optional

• A focus on AI/ML solutions.
• A Bachelor’s or Master’s degree in Data Science, Computer Science, Economics, or a related discipline.

Your 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.
• Optimize environment performance, logging, and reward reproducibility across distributed setups.