Health AI Engineer Intern
About The Position
At Boston Scientific, we’ll give you the opportunity to harness all that’s within you by working in teams of diverse and high-performing employees, tackling some of the most important health industry challenges. With access to the latest tools, information and training, we’ll help you in advancing your skills and career. Here, you’ll be supported in progressing – whatever your ambitions. At Boston Scientific, we value collaboration and synergy. This role follows a hybrid work model, requiring employees to be in our local office at least three days per week. Relocation and housing assistance may be available to those who meet the eligibility criteria. Boston Scientific will not offer sponsorship or take over sponsorship of an employment VISA for this position at this time We will consider qualified applicants of all ages who are starting (or restarting) their careers As a Health AI Engineer Intern, you will support the design, development, evaluation, and deployment readiness of AI/ML solutions that improve clinical and product outcomes. You will work with cross-functional partners (data science, clinical, regulatory, quality, cybersecurity, product, and platform teams) to build practical, scalable, and governed AI capabilities, with an emphasis on medical imaging and early product development.
Requirements
- Must graduate between Fall 2026 – Spring 2028 (rising seniors and juniors)
- Currently pursuing a bachelor’s or graduate level degree in Computer Engineering, Data Science, or Biomedical Engineering
- Must be able to commit to one of the following full internship program periods: May 18th – August 7th OR May 26th – August 14th
- Must be eligible to work in the U.S. without company sponsorship, now or in the future, for employment-based work authorization
- Must have reliable transportation to and from the Marlborough, MA Boston Scientific Corporate location
Nice To Haves
- Ability to communicate effectively and collaborate with diverse, cross-functional teams; strong documentation habits (clear code comments, experiment notes, and technical summaries).
- Interest in healthcare AI and learning in regulated, safety-critical environments; attention to data privacy, security, and Responsible AI practices.
- Experience with common ML tooling and basic software engineering practices (testing, code review) through coursework or projects.
- Preferred: familiarity with medical imaging (DICOM), clinical data concepts, or MLOps tools through projects, research, or internships.
Responsibilities
- Support data acquisition, cleaning, and curation for healthcare AI projects (e.g., DICOM images, annotations/labels, and associated metadata) under guidance from senior engineers.
- Implement and improve preprocessing and feature engineering pipelines; contribute code to reproducible training and evaluation workflows (versioned datasets, experiments, and model artifacts).
- Assist with developing and tuning imaging and/or multimodal models (e.g., detection, segmentation, classification, quantification) using modern ML/deep learning frameworks.
- Execute evaluation plans using clinically meaningful metrics; perform error analysis, robustness checks, and subgroup performance assessment with mentorship from the team.
- Contribute to MLOps and production-readiness activities such as automated testing, containerization, CI/CD support, model packaging, documentation, and basic monitoring/observability tasks.
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What This Job Offers
Job Type
Full-time
Career Level
Intern
