Job Description 

Candidate will work on:  

Design, prototype, and evaluate AI agents that automate data science tasks (e.g., data wrangling, visualization, modeling).  Develop benchmark datasets, tasks, and metrics for evaluating AI agents in realistic data science scenarios.  Conduct empirical studies and ablation experiments to validate design choices and performance.  Contribute to building reproducible pipelines and documentation for agent evaluation.  Publish findings internally or externally (e.g., open-source repositories / benchmarks, academic conferences). 

 

Qualifications 

Currently pursuing a PhD in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related field.  Strong research background in one or more of the following: AI agents and autonomous systems, data science automation, benchmarking and evaluation methodology, LLMs.   Proficient in Python and familiarity with open-source tools/libraries for data science.  Excellent analytical, problem-solving, and communication skills.  Publication record in top AI/ML conferences  Knowledge of LLM-based agents (e.g., LangChain, AutoGen) is a plus.   Experience working with structured datasets and data-centric AI workflows is a plus.