AI/ML Research Associate

Analytical Mechanics Associates•Hampton, VA

9d•$23 - $34

About The Position

NASA Langley Research Center is seeking high-performing students with demonstrated expertise in Artificial Intelligence and Machine Learning (AI/ML) to join the AiTHENA Program—Artificial Intelligence Training and Hands-on Experience at NASA. As an AiTHENA Research Associate, you will work directly alongside NASA scientists, engineers, and civil servants to integrate cutting-edge AI/ML techniques into mission-driven research and federal business operations. This is a unique opportunity to contribute to active projects that support NASA’s strategic goals Overview AiTHENA supports NASA researchers by pairing high-impact projects with AI/ML and data talent to accelerate mission-relevant tools. We are seeking an AI/ML Associate / Early Career Professional (ECP) with interest in AI governance, risk analysis, and applied data support to help NASA teams build practical, responsible AI capabilities, workflows, and implementation strategies. This position is a good fit for someone who may not have deep technical or research experience yet, but can learn quickly, follow structured guidance, and communicate clearly. You’ll work closely with a NASA mentor to translate needs into clear tasks, build reusable artifacts, and support governance-aligned workflows. Remote and in-person candidates will be considered. Hourly pay range: $23.10 – $33.50 (depending on locality)

Requirements

Bachelor’s degree in a related field (Engineering, Math, Science, Computer Science, Information Systems, Policy/Program Management with technical exposure, or similar) or equivalent practical experience.
Interest in responsible AI / AI governance and comfort working with structured checklists and documentation.
Comfort learning technical tools (you don’t need to be an expert).
Basic experience with Python or strong willingness to learn quickly.
Familiarity with common data formats (CSV/Excel, text files) and attention to detail.
Ability to communicate clearly in writing and presentations (notes, short readouts, simple memos).
Strong organization and follow-through (track tasks, meet deadlines, ask for help early).
Work authorization: In-person: U.S. Citizenship or Permanent Residency required Remote: open to individuals authorized to work in the U.S.

Nice To Haves

Some exposure (coursework, projects, internships) to one or more of: AI governance concepts (model cards, data documentation, risk assessment basics, evaluation/monitoring ideas) Data cleaning and analysis (pandas, Excel, basic SQL) Simple machine learning with scikit-learn Data visualization (matplotlib/plotly) Working with text data (document tagging, keyword extraction, search)
Familiarity with Git (version control) or willingness to learn it.
Experience working with process workflows (Jira/ADO/Trello/SharePoint) and building simple trackers/dashboards.
Graduate students (MS/PhD), recent graduates, or career transitioners are welcome.

Responsibilities

AI Governance Support Help teams document and track AI-related work using simple, repeatable processes.
Support an AI use-case process by collecting key details (purpose, users, data types, risks, constraints).
Create and maintain governance artifacts, such as: model/data “factsheets” (basic model cards, dataset summaries) decision logs and traceability notes checklists for responsible AI (data handling, evaluation notes, limitations)
Assist with risk triage (not legal decisions—supporting documentation and routing): flagging common considerations like sensitive data, privacy, misuse risk, and monitoring needs.
Help organize and communicate governance readiness for demos or reviews (briefs, slide summaries, status dashboards).
Applied Data + Prototype Support Prepare and organize data: collect, clean, format, and document datasets (CSV/Excel, logs, text, images).
Run basic analyses using Python (or similar tools): summaries, charts, simple quality checks.
Support AI/ML work by running established workflows, such as: baseline models (classification/regression) simple trend checks for time-series data basic text processing (tagging, search, summarization with guardrails)
Create and share prototypes such as notebooks, scripts, simple dashboards, or small utilities that a mentor team can reuse.
Keep work reproducible and easy to follow clear file organization, notes, and step-by-step documentation.
Participate in AiTHENA check-ins, technical exchanges, demos, and closeout deliverables.