Machine Learning Internship Summer 2027

CoVar

Durham, NC · HybridInternshipPosted 2w agoStill listed 1 day ago

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At a glance

Compensation
No compensation found
Location
Durham, NCHybrid
Role Type
Internship
Schedule
Internship
Work Authorization
US work authorization required

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Requirements

Credentials this posting asks for.

Bachelor's degree

Job overview

CoVar is a small mission‑driven AI/ML R&D software company seeking interns for an 8‑12‑week, in‑person program in Durham, NC. Interns will develop software and machine‑learning algorithms, work with data, write production code, and present results to customers, while receiving mentorship and a competitive hourly wage.

Skills & qualifications

RequiredNice to have

Skills

PythonNumPyPandasGitPyTorchMachine Learning FundamentalsGradient DescentCross‑ValidationROC CurvesConfusion MatricesTechnical CommunicationComputer VisionSupport‑Vector‑MachinesLogistic RegressionResNetResNextYOLOCenterNetImage SegmentationVision Image TransformersVision Language ModelsNatural Language ProcessingBayesian Models

Qualifications

Pursuing Bachelor's in Engineering, Math, Computer Science or Related FieldUS Citizenship

Full job description

About CoVar

CoVar is a small, mission-driven AI/ML R&D software company based in Durham, NC and McLean, VA. We build advanced software and machine learning systems that help the DoW detect threats in high-stakes environments and enable biomedical researchers to accelerate discoveries that save lives. Our team is composed of curious, passionate engineers who care deeply about using AI to solve real-world problems that matter.

Internship Overview

  • 8-12 weeks – flexible, depending on your schedule

  • In-person in Durham, NC

  • Competitively paid internship

  • Matched with one project based on your current expertise and interests

  • Paired with an advisor or project lead who will guide you and help you set and meet your goals

  • Concludes with you presenting your work either internally to CoVar or externally to the customer

Interview Timeline

  • Accepting applications online from now to mid-November 2026

  • Interviews starting in September 2026

  • Interview steps consist of a video screening and a code screening

  • Offers out by end of November 2026

About the position

You will help CoVar develop software and machine learning algorithms to solve real-world customer problems. You will work with data, develop algorithms, evaluate results, and write the production code that goes onto real-world systems. You may have the opportunity to present your work to high-level customers in the DoW and in the industry.

Qualifications

Applicants should have expertise in Python (including NumPy, pandas, and other packages) and PyTorch. Deep understanding of machine learning fundamentals (gradient descent, cross-validation, ROC curves, confusion matrices) are necessary. Knowledge of classical machine learning (e.g., support-vector-machines, logistic regression) are valued. Applicants are ideally familiar with some computer vision algorithms (e.g., for object classification (ResNet, ResNext), object detection (e.g., YOLO, CenterNet), or image segmentation) and/or other modern image processing AI/ML techniques (vision image transformers, vision language models, etc.). Previous experience with DoW customers is a plus.

Minimum qualifications

  • Software expertise: Python and associated numerical and analytics packages (NumPy, pandas, etc.); git; PyTorch.

  • AI/ML expertise: Machine learning fundamentals; Deep knowledge of state-of-the-art in any of the following: computer vision (preferred), natural language processing, classical machine learning, Bayesian models, etc.

  • Pursuing B.S., preferably M.S. or Ph.D in engineering, math, computer science, or related field

  • Excellent technical communication skills

  • Ability to work in Durham, NC (relocation assistance available)

  • Work authorization: US citizen

Bonus skills

  • Department of War project experience

Benefits

  • Competitive hourly wages

  • Flexible work schedule

  • Hybrid policy (in office at least 3x per week)

Email us: [email protected] Visit us: www.covar.com

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