BNY
AI / Machine Learning Intern
InternshipWork from HomeKolkata, West Bengal6 months22K/mo3 openingsImmediate / Rolling
About this internship
BNY has an open AI / Machine Learning Intern position in Kolkata for motivated freshers and final-year students. You will work on live applied AI and machine learning projects and finish with something you can genuinely talk about in interviews.
About the role
As an AI / Machine Learning Intern at…
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Skills you'll use
PythonMachine LearningDeep LearningPyTorch / TensorFlowScikit-learnPandasFeature EngineeringModel EvaluationSQLMLOps Basics
What you'll do
- Work on training, evaluating and deploying models alongside the core team
- Apply Python, Machine Learning, Deep Learning, PyTorch / TensorFlow 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/MCA/M.Sc (CS, Statistics, Maths) — 2026 freshers & final-year students welcome
- Working knowledge of Python, Machine Learning, Deep Learning (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 Kolkata, West Bengal
Perks & benefits
Live project experienceExposure to professional tools and workflowsPre-Placement Offer (PPO) opportunityFlexible working hoursNetworking with senior professionals
Interview & selection process
2 rounds — typical selection flow for this role:
- 1Application screening & resume shortlisting by the talent team
- 2Online aptitude / domain assessment
About BNY
BNY operates in the asset & wealth management sector and has an active presence in Kolkata. 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…
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