Machine Learning and A.I. Intern - Undergraduate Students
About The Position
We are looking for undergraduate junior and senior level students majoring in Computer Science or a related discipline for a 12-week internship role in Gaithersburg, MD from May 18th to August 7th. Position Duties: Working with Intern Manager to understand: Current process to forecast Full Time Employee (FTE) resources for Analytical Sciences including governance process and major pain points. Current MYTIME guidance and how FTE variance is assessed. Major factors that impact FTE resourcing. Major CMC activities. Current databases of MYTIME data and underlying metadata. Independent work to write code to: Model FTE resources based on historical projects to predict resource requirements for each CMC activity per skill. Develop user interface to ingest user input for the key factors. Predict FTE resources for CMC projects per quarter based on the limited user input and model. Incorporate new data to continuously improve models as we gain more expertise with certain modalities/improve efficiency of development. Provide detailed documentation so the work can be continued and refined after the internship.
Requirements
- Undergraduate junior and senior level students majoring in Computer Science or a related discipline.
- Candidates must have an expected graduation date after August 2026.
- Understanding of machine learning and artificial intelligence is required.
- Programming experience including developing tools or models independently and building scripts either in an academic or professional setting is required.
- Ability to report onsite to Gaithersburg, MD 4-5 days per week.
- US Work Authorization is required at time of application.
Nice To Haves
- Software exposure to Excel and Power BI is preferred.
- Previous experience building prototypes or contributing to digital transformation project is preferred.
Responsibilities
- Working with Intern Manager to understand current process to forecast Full Time Employee (FTE) resources for Analytical Sciences including governance process and major pain points, current MYTIME guidance and how FTE variance is assessed, major factors that impact FTE resourcing, major CMC activities, and current databases of MYTIME data and underlying metadata.
- Independently write code to model FTE resources based on historical projects to predict resource requirements for each CMC activity per skill.
- Develop user interface to ingest user input for the key factors.
- Predict FTE resources for CMC projects per quarter based on the limited user input and model.
- Incorporate new data to continuously improve models as we gain more expertise with certain modalities/improve efficiency of development.
- Provide detailed documentation so the work can be continued and refined after the internship.
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What This Job Offers
Career Level
Intern
Number of Employees
5,001-10,000 employees
