AI/ML Research and Development Intern

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• CURRENT PENN STATE STUDENT (not employed previously at the university) and seeking employment with Penn State, please login to Workday to complete the student application process. Please do not apply here, apply internally through Workday.

• If you are NOT a current employee or student, please click “Apply” and complete the application process for external applicants.

Approval of remote and hybrid work is not guaranteed regardless of work location. For additional information on remote work at Penn State, see Notice to Out of State Applicants.

JOB DESCRIPTION AND POSITION REQUIREMENTS:

We are seeking several undergraduate students with artificial intelligence/ machine learning (AI/ML) experience to join Visualization and Decision Support Division of the Applied Research Laboratory (ARL) at Penn State. looking to support our mission to discover, demonstrate, transition, and educate.  Interns will have the opportunity to work on cutting-edge AI technologies, participate in a Kaggle-style competition, and develop solutions to problems in computer vision and geospatial understanding.

Students selected will serve as active, hands-on, contributing members of the research staff at ARL. As part of this position, the candidate may:

• Work within an agile development environment with other 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, with a focus on machine learning and artificial intelligence.
• Contribute to the development, testing, and transition of front and back-end software applications to various IT environments.
• Support machine learning model development using tools and technologies such as: PyTorch, Pandas, PostgreSQL, AWS, Docker and similar technologies.
• Collaborate with cross-functional teams to integrate machine learning models into existing systems and develop new ones to meet specific project needs.

Students studying Computer Science, Electrical Engineering or Mathematics are encouraged to apply.

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.

Candidates selected may be subject to a government security investigation. You must be a U.S. citizen to apply. Employment with the Applied Research Laboratory will require successful completion of a pre-employment drug screen.

ARL is committed to diversity, equity, and inclusion; we believe this is central to our success as a Department of Defense designated University Affiliated Research Center (UARC).  We are at our best when we draw on the talents of all parts of society, and our greatest accomplishments are achieved when diverse perspectives are part of our workforce.

FOR FURTHER INFORMATION on ARL, visit our web site at www.arl.psu.edu

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Pursuant to the Jeanne Clery Disclosure of Campus Security Policy and Campus Crime Statistics Act and the Pennsylvania Act of 1988, 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. The ASR is available for review here.

Employment with the University will require successful completion of background check(s) in accordance with University policies. 

EEO IS THE LAW

Penn State is an equal opportunity, affirmative action 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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