AI/ML Research Associate

What You’ll Do

• 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.

Required Qualifications

• 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.

Preferred Qualifications

• Experience with one or more of the following: Time series modeling, forecasting, and anomaly detection, NLP (document classification, information extraction, RAG-style workflows), Computer vision (segmentation, detection, image enhancement), Physics-informed ML or surrogate modeling, Experiment design and uncertainty quantification, Familiarity with software engineering practices: Git-based workflows, unit testing, code review, packaging; Containerization (Docker) and/or workflow automation, Experience with cloud/HPC environments and MLOps concepts (CI/CD, model versioning, monitoring), Exposure to “high assurance” or safety/mission-relevant development practices (traceability, verification, controlled environments).
• Graduate students enrolled in a PhD or Master's program in Computer Science, Data Science, or related fields or career transitioners/early career professionals.
• Living within a reasonable commuting distance from NASA center for project selected for: Langley Research Center in Hampton, VA, NASA Katherine Johnson IV&V Facility in West Virginia, NASA Ames Research Center in Mountain View, Ca, or NASA HQ in Washington, D.C.

Benefits

Competitive salaries and a substantial benefits package, including but not limited to:

• Paid personal and federally recognized holiday leave
• Salary deferrals into a 401(k)-matching plan with immediate vesting
• Tuition reimbursement
• Short/long term disability plans
• A variety of medical, dental, and vision insurance options

AMA is committed to the professional growth of every employee, understanding that the successes of our employees drive our success. We provide a work environment that is engaging, collaborative, and supportive.

To learn more about our company, please visit our website at www.ama-inc.com/careers and follow us on Facebook and LinkedIn.

AMA is an Equal Opportunity Employer and does not discriminate against any applicant for employment or employee because of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veteran status, or any other characteristic prohibited under federal, state, or local laws.