Collaborate with NASA project mentors and technical teams to define AIML problem statements, success metrics, and validation plans.
Develop and evaluate ML models (e.g., regression/classification, time series, anomaly detection, NLP, computer vision—based on project needs).
Build reproducible data pipelines for ingestion, cleaning, feature engineering, labeling, and dataset versioning.
Prototype and deliver proof-of-concept tools (scripts, notebooks, small applications, dashboards, or APIs) that can be transitioned to the mentor team.
Apply sound practices for experimentation: baselines, ablation studies, cross-validation, and uncertainty/error analysis.
Document methods, assumptions, limitations, and recommendations in clear technical writeups.
Contribute to best practices for trustworthy/robust ML (data leakage prevention, bias checks, model monitoring considerations, and traceability).
Participate in AiTHENA technical exchanges, demos, and closeout deliverables.

Bachelor’s degree (or higher) in Computer Science, Engineering, Applied Math, Data Science, Physics, or a related field—or equivalent demonstrated experience.
Demonstrated experience building AIML models and evaluating performance using appropriate metrics.
Proficiency with Python and common data/ML tooling (e.g., NumPy, pandas, scikit-learn; familiarity with PyTorch or TensorFlow is a plus).
Experience working with real-world datasets (messy data, missing values, outliers, labeling challenges).
Ability to communicate technical content clearly (documentation, presentations, or technical memos).
Strong organizational skills and the ability to manage tasks independently in a fast-paced research environment.
U.S. Citizenship or Permanent Residency required for in-person positions.

AIML Research Associate

Key skills