The Applied Research Laboratory at Penn State University→
AI/ML Research and Development Intern at The Applied… · Reston
InternshipOn-siteReston, VA
Skills
artificial intelligencemachine learningcomputer visiongeospatial understandingagile developmentpytorchpandaspostgresqlawsdocker
Job Description
Summary: The Applied Research Laboratory at Penn State University is seeking graduate students with AI/ML experience to join their Visualization and Decision Support Division. Interns will work on cutting-edge AI technologies and contribute to the development of algorithmic solutions for various sponsor requirements.
Responsibilities:
- 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
Required Qualifications:
- Must have a bachelor's degree and be enrolled in a master's or higher level degree program
- Experience in Machine Learning is preferred
- Ability to obtain a government security clearance
- Must be a U.S. citizen to apply
- Successful completion of background check(s) in accordance with University policies
- Successful completion of a pre-employment drug screen
Preferred Qualifications:
- Students studying Computer Science, Electrical Engineering or Mathematics are encouraged to apply
Required Skills: Artificial Intelligence, Machine Learning, Computer Vision, Geospatial Understanding, Agile Development, PyTorch, Pandas, PostgreSQL, AWS, Docker