Remote job
Machine Learning Intern/Co-op
Job details
About this role
Role overview This internship or co-op places candidates directly within applied machine learning teams working on AI-powered pathology, contributing to projects with a direct line to the technical roadmap and patient impact. The role is embedded within product and core ML teams, partnering with scientists, engineers, and product managers to translate clinical needs into scalable ML solutions.
Responsibilities - Contribute to the design, development, and evaluation of machine learning models for AI products, AI services, and core ML models - Work on subprojects drawn from the active ML product roadmap, exploring model improvements with novel techniques - Partner with MLOps and platform teams to help build and improve ML pipelines - Participate in experimental design, analysis, and team knowledge-sharing through design reviews, technical forums, and journal clubs
Requirements - Currently enrolled in an M.S. or Ph.D. program in Computer Science, Electrical Engineering, or Biomedical Engineering with a focus on computer vision and machine learning - Strong programming skills in Python and hands-on experience with ML frameworks such as PyTorch or TensorFlow - Demonstrated understanding 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 - Passion for improving patient outcomes
Nice to have - Prior experience working on complex open-source projects or AI-based products - Participation in student organizations or other leadership activities - Contributions to AI or ML publications
Benefits and work setup - Fall 2026 / Winter 2027 timeline with a 3–6 month commitment, 4–6 months preferred - Primary locations in Boston, MA and New York, NY, with potential for remote US-based candidates; onsite 3 days per week highly preferred - Expected hourly rate of $55–$70 based on Boston, MA, with actual pay determined by experience, qualifications, and location - Paid holiday time off during the internship