13 hours ago
Base Salary
$170k - $400k/yr
Responsibilities
- Build frontend interfaces, backend services, APIs, data models, tools, and realistic workflows for AI-agent training and evaluation environments.
- Develop agent-gym infrastructure for orchestration, sandboxing, packaging, benchmarking, and execution across heterogeneous targets.
- Create interconnected, stateful simulations spanning websites, apps, and artifacts with dynamic content and events.
- Integrate environments with RL training and evaluation pipelines, including reusable agent interfaces, lifecycle APIs, and trajectory and artifact collection.
- Support thousands of concurrent sandboxed environments with isolation, consistent state, snapshots, resets, and partial-failure recovery.
- Improve startup and teardown latency, scheduling, resource utilization, throughput, observability, debugging, and reproducibility.
Requirements
- Strong full-stack engineering skills across frontend interfaces, backend services, APIs, and data models.
- Experience with stateful backend or distributed systems, including databases, queues, caching, concurrency, consistency, and failure recovery.
- Strong algorithms and systems fundamentals, including profiling workloads, identifying bottlenecks, and validating performance improvements.
- Ability to design reusable APIs and abstractions for integrating, extending, and operating complex environments.
- Careful debugging and testing practices focused on application fidelity, state transitions, reproducibility, and failure detection.
- Ability to handle ambiguous problems, translate real software behavior into simulations, collaborate with researchers, and learn the agent and RL systems being supported.
- Experience with RL rollout systems, agent training pipelines, evaluation harnesses, containers, virtual machines, sandbox runtimes, orchestration systems, browser automation, computer-use agents, simulation frameworks, or event-driven dynamic systems is preferred.
Benefits
- Full-time position.
- Additional benefits and compensation components may be included in the total compensation package and shared if an employment offer is extended.
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