AI/ML Research Associate
2 weeks ago
Job Description:
NASA Langley Research Center is seeking high-performing students with demonstrated expertise in Artificial Intelligence and Machine Learning (AI/ML) to join the AiTHENA Initiative—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 while gaining real-world experience in a federal research environment.
This position pays $12-$27 an hour based on education and location where work is performed.
Onsite work in Hampton, VA is strongly preferred but telework could be considered for qualified applicants on a case by case basis.
Additional Details:
- This is a paid 10-week assignment
- Selected candidates will participate in a bootcamp, receive mentorship, and deliver a capstone project
- Opportunities exist to share findings and train civil servants on new tools and methods
Why Apply?
- Apply your AI/ML expertise to solve complex, real-world problems with national impact
- Collaborate with multidisciplinary teams across science, engineering, and technology
- Work with NASA mentors and contribute directly to ongoing research efforts
- Train on NASA platforms and tools (e.g., Google Cloud Platform, K-Cluster, Azure)
- Gain experience in federal workflows and upskill NASA's workforce through knowledge-sharing
Required Qualifications:
- Students currently enrolled in a PhD or Master's or undergrad program in Computer Science, Data Science, or related fields
- Specialization or research focus in AI/ML techniques and applications
- Strong technical and problem-solving skills
- Excellent communication and collaboration abilities
- Interest in public service, applied research, and federal innovation
- U.S. Citizenship or Permanent Residency required
- Currently a current undergrad or graduate student at a 4 year educational institution in Alabama and/or permanent Alabama resident.
Desired Qualifications:
- Graduate students enrolled in a PhD or Master's program in Computer Science, Data Science, or related fields
- Living within a reasonable commuting distance from NASA Langley Research Center in Hampton, VA
Apply now to become part of a transformational workforce program that accelerates NASA research and empowers the next generation of AI/ML leaders.
Analytical Mechanics Associates (AMA) is proud of our customer relationships, our diverse and dynamic work environment, and our employees' career satisfaction. AMA is a small business with a wide reach; headquartered in Hampton, VA, AMA has operations in Greenbelt, MD; Huntsville, AL; Dallas and Houston, TX; Denver, CO; Mountain View, CA; and Edwards Air Force Base, CA. With over 60 years of experience, AMA specializes in aerospace engineering, science, analytics, information technology, and visualization solutions. AMA combines the best of engineering, science, and mathematics capabilities with the latest in information technologies, visualization, and multimedia to build creative solutions. We offer 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, and 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..
AMA is an Affirmative Action/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.
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