Job Description::
* Hands-on reinforcement learning experience.
* Experience using LLMs for agents, evaluation, reasoning, automation, or benchmark workflows.
* Strong Python experience for ML, data workflows, experimentation, and analysis.
* Experience designing and running experiments with statistical and analytical rigor.
* Strong understanding of evaluation metrics, scoring frameworks, performance comparison, and benchmark design.
* Experience analyzing structured logs, run outputs, model/agent performance, and experiment results.
* Ability to work across APIs, logs, CLI/tools, data structures, and platform workflows.
* Strong communication skills to translate experiment findings into platform improvement requirements.
* Ability to work inside client-owned repositories, infrastructure, workflows, and security controls.
Preferred Skills
* Experience with game environments, simulation environments, Gym-like interfaces, RL environments, or agentic AI test harnesses.
* Experience benchmarking LLM agents, RL policies, autonomous agents, or hybrid AI systems.
* Experience with experiment tracking, run comparison tools, metrics dashboards, or evaluation pipelines.
* Experience with prompt engineering, agent orchestration, tool use, and LLM evaluation frameworks.
* Experience with data visualization and performance analytics.
* Experience working with externally developed algorithms, reproducible experiments, and version-controlled evaluation workflows.
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