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AI​/ML Research and Development Intern

Job in University Park, Dallas County, Texas, USA
Listing for: The Applied Research Laboratory at Penn State University
Full Time, Part Time, Apprenticeship/Internship position
Listed on 2026-04-24
Job specializations:
  • Software Development
    Data Scientist, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 10000 - 60000 USD Yearly USD 10000.00 60000.00 YEAR
Job Description & How to Apply Below

APPLICATION INSTRUCTIONS

  • Current Penn State employee (faculty, staff, technical service, or student): please log on to Workday to complete the internal application process. Do not apply here.
  • Current Penn State student (not employed previously at the university): please log on to Workday to complete the student application process. Do not apply here.
  • External applicants: click "Apply" and complete the application process for external candidates.
JOB DESCRIPTION AND POSITION REQUIREMENTS

We are seeking graduate students with artificial intelligence / machine learning (AI/ML) experience to join the Visualization and Decision Support Division of the Applied Research Laboratory (ARL) at Penn State. Interns will work on cutting‑edge AI technologies, participate in a Kaggle‑style competition, and develop solutions to problems in computer vision and geospatial understanding. Students studying Computer Science, Electrical Engineering, or Mathematics are encouraged to apply.

  • Work within an agile development environment with developers, scrum master, and product owners to scope, develop, and deliver quality software solutions.
  • Contribute to the research and development of unique algorithmic solutions for a wide array of sponsor requirements, focusing on machine learning and artificial intelligence.
  • Develop, test, and transition front‑ and back‑end software applications to various IT environments.
  • Support machine learning model development using tools and technologies such as PyTorch, Pandas, Postgre

    SQL, AWS, Docker, and similar tools.
  • Collaborate with cross‑functional teams to integrate machine learning models into existing systems and develop new ones to meet specific project needs.

Must have a bachelor’s degree and be enrolled in a master’s or higher level degree program. Experience in machine learning is preferred.

Internship hours: up to 20 hours/week during fall and spring semesters; 40 hours/week over the summer. This is a paid internship located at either State College, PA or Reston, VA. Relocation and housing are not provided.

EXPERIENCE IN MACHINE LEARNING IS PREFERRED

Successful candidates will work up to 20 hours/week during the fall and spring semesters and 40 hours/week over the summer. This is a paid internship located at either State College, PA or Reston, VA. Relocation and housing are not provided.

BACKGROUND CHECKS/CLEARANCES

Employment will require successful completion of background checks in accordance with University policies. All positions at ARL require the ability to obtain a government security clearance; you will be notified during the interview process if this position is subject to a government background investigation. You must be a U.S. citizen to apply. Employment will also require a pre‑employment drug screen.

CAMPUS SECURITY CRIME STATISTICS

Pursuant to the Jeanne Clery Disclosure of Campus Security Policy and Campus Crime Statistics Act, Penn State publishes a combined Annual Security and Annual Fire Safety Report (ASR). The ASR includes crime statistics and institutional policies concerning campus security, such as those concerning alcohol and drug use, crime prevention, the reporting of crimes, sexual assault, and other matters.

EEO IS THE LAW

Penn State is an equal‑opportunity employer and is committed to providing employment opportunities to all qualified applicants without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. If you are unable to use our online application process due to an impairment or disability, please contact 814‑865‑1473.

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