Wysa

Medical AI Intern

InternshipHybridGhaziabad, Uttar Pradesh2 months33K/mo1 openingImmediate / Rolling

About this internship

Join Wysa in Ghaziabad as a Medical AI Intern. This entry-level internship is designed for students and recent graduates who learn best by building, shipping and getting real feedback on medical AI work. About the role As a Medical AI Intern at Wysa, your core focus will be building and validating…

Skills you'll use

PythonDeep LearningMedical ImagingPyTorchModel ValidationDICOM BasicsStatisticsData AnnotationRegulatory AwarenessTechnical Writing

What you'll do

Work on building and validating models on medical imaging or clinical text alongside the core team
Apply Python, Deep Learning, Medical Imaging, PyTorch to live, production-facing problems
Document your work clearly for reviewers and stakeholders
Participate in reviews and act on the feedback you receive
Collaborate across engineering, product, design or business as required
Follow the team's quality, testing and documentation standards

Who can apply

Pursuing or recently completed B.E./B.Tech/M.Tech/M.Sc/MBBS with a data interest — 2026 freshers & final-year students welcome
Working knowledge of Python, Deep Learning, Medical Imaging (or a genuine willingness to learn them)
Strong fundamentals in your discipline and clear problem-solving ability
Care with detail and the discipline to document your work
Clear written and verbal communication in English
Based in or willing to work from Ghaziabad, Uttar Pradesh

Perks & benefits

Flexible working hoursNetworking with senior professionalsInternship CertificateLetter of RecommendationMentorship from a named mentor

Interview & selection process

3 rounds — typical selection flow for this role:

1Application screening & resume shortlisting by the talent team
2Team-fit / behavioural interview with the team
3HR discussion — stipend, start date, expectations and offer

About Wysa

Wysa operates in the healthtech sector and has an active presence in Ghaziabad. Interns here are put on real work from the start, because the team's view is that the fastest way to learn a craft is to practise it under people who already do it well — not to watch it from a distance. The work runs…

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