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Easebuzz logo — Easebuzz Machine Learning Engineer Intern in Kolkata, West Bengal
Easebuzz VerifiedActively Hiring

Machine Learning Engineer Intern

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Location

Kolkata, West Bengal

Work Mode

Hybrid

Duration

3 months

Stipend

₹17,000/mo

Start Date

Immediate / Rolling

Openings

4 positions

Type

Full-time

Category

Machine Learning

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About the Internship

Join Easebuzz in Kolkata as a Machine Learning Engineer Intern. This entry-level internship is designed for students and recent graduates who learn best by building, shipping and getting real feedback on applied machine learning work. About the role As a Machine Learning Engineer Intern at…

About Easebuzz

Easebuzz offers a mentor-led Machine Learning Engineer Intern in Kolkata with live project work in machine learning, a stipend of ₹17,000/month and a Pre-Placement Offer opportunity for strong performers.
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Kolkata, West BengalVerified employer4 openings
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Skills Required

PythonScikit-LearnTensorFlow or PyTorchFeature EngineeringModel Evaluation MetricsPandas & NumPySQLModel DeploymentCross-ValidationGit & GitHub

Who Can Apply

  • Final-year students and recent graduates from B.E./B.Tech (CSE/IT/ECE/AI-ML), BCA, MCA, M.Sc (CS / Statistics) or M.Tech who are based in or willing to work from Kolkata. You should be keen to learn Python, Scikit-Learn, TensorFlow or PyTorch on real projects and able to write clearly. Freshers are welcome — no prior work experience is required, and a strong project portfolio matters more than a long CV.

Perks

Mentorship from a named mentorLive project experienceExposure to professional tools and workflowsPre-Placement Offer (PPO) opportunityFlexible working hours

Interview & Selection Process

3 rounds — typical selection flow for this role:

  1. 1Application screening & resume shortlisting by the talent team
  2. 2Team-fit / behavioural interview with the team
  3. 3HR discussion — stipend, start date, expectations and offer
17,000/month

Stipend · 3 months

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Openings4 positions
Applicants0 applied
ModeHybrid
CategoryMachine Learning
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