Research Professional I, Computer Science (Temporary)
University of Arizona3 days ago
Tucson, AZ, USAEntry Level
Responsibilities
- Implement and evaluate a basic Monte Carlo Tree Search algorithm in benchmark reinforcement learning environments.
- Implement supervised fine-tuning and other basic imitation learning algorithms and evaluate them in benchmark environments.
- Develop and evaluate a reinforcement learning algorithm based on the outcomes of the preceding tasks.
- Maintain training-pipeline source code, document code, prepare usage manuals, and identify library dependencies.
- Generate algorithm-performance evaluation plots and visualize Monte Carlo Tree Search agent reasoning traces.
- Collaborate with internal departments to share information and improve data-handling processes.
Requirements
- Knowledge of maintaining code for libraries, APIs, deep learning, and reinforcement learning pipelines.
- Ability to generate evaluation plots and visualize Monte Carlo Tree Search agent reasoning traces.
- Ability to translate technical concepts into clear documentation and collaborate across multidisciplinary teams.
Categories
AI Research