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Machine Learning Intern/Co-op (Spring/Summer 2026)

Remote, USA Full-time Posted 2025-11-24

PathAI is dedicated to improving patient outcomes with AI-powered pathology. The Machine Learning Intern/Co-op will work directly with the AI product and ML Core teams, contributing to the design and development of machine learning models that impact patient outcomes.


Responsibilities

  • Contribute to the design, development, and evaluation of machine learning models for our AI products, AI services and core ML models
  • Work on subprojects derived from our ongoing ML product roadmap, focusing on areas like model improvements with novel techniques
  • Partner with our MLOps and platform teams to help build and improve our ML pipelines
  • Participate in experimental design, analysis, and team knowledge-sharing initiatives like design reviews, technical forums and journal clubs

Skills

  • Currently pursuing a M.S., or Ph.D. in Computer Science, Electrical Engineering, Biomedical Engineering with a focus on Computer Vision and Machine Learning
  • Strong programming skills in Python and hands-on experience with ML frameworks (e.g., PyTorch, TensorFlow)
  • A solid grasp of the fundamentals of machine learning and/or computer vision
  • Excellent communication skills and a desire to work in a highly collaborative, cross-functional environment
  • A passion for our mission to improve patient outcomes
  • Any high impact contributions through any AI/ML publications, open-source projects and any AI based products

Company Overview

  • PathAI develops technology that assists pathologists in making accurate diagnoses for every patient, every time. It was founded in 2016, and is headquartered in Boston, Massachusetts, USA, with a workforce of 501-1000 employees. Its website is http://www.pathai.com.

  • Company H1B Sponsorship

  • PathAI has a track record of offering H1B sponsorships, with 7 in 2025, 20 in 2024, 21 in 2023, 29 in 2022, 25 in 2021, 7 in 2020. Please note that this does not guarantee sponsorship for this specific role.

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