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Delhivery logo — Delhivery Recommendation Systems Intern in Hubballi, Karnataka
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Recommendation Systems Intern

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Location

Hubballi, Karnataka

Work Mode

In Office

Duration

4 months

Stipend

₹25,000/mo

Start Date

Immediate / Rolling

Openings

6 positions

Type

Full-time

Category

Machine Learning

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About the Internship

Join Delhivery in Hubballi as a Recommendation Systems Intern. This entry-level internship is designed for students and recent graduates who learn best by building, shipping and getting real feedback on recommendation and personalisation systems work. About the role As a Recommendation Systems…

About Delhivery

Delhivery offers a mentor-led Recommendation Systems Intern in Hubballi with live project work in machine learning, a stipend of ₹25,000/month and a Pre-Placement Offer opportunity for strong performers.
Hubballi, KarnatakaVerified employer6 openings
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Skills Required

Recommendation SystemsCollaborative FilteringPythonRanking ModelsEmbeddingsA/B TestingSQLCold-Start HandlingEvaluation (NDCG / CTR)Feature Engineering

Who Can Apply

  • Final-year students and recent graduates from B.E./B.Tech (CSE/IT), MCA, M.Sc (CS / Statistics) or M.Tech who are based in or willing to work from Hubballi. You should be keen to learn Recommendation Systems, Collaborative Filtering, Python 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

4 rounds — typical selection flow for this role:

  1. 1Application screening & resume shortlisting by the talent team
  2. 2Practical assignment or case study with a short walkthrough
  3. 3Discussion with the hiring manager on the role and your fit
  4. 4HR discussion — stipend, start date, expectations and offer
25,000/month

Stipend · 4 months

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Openings6 positions
Applicants0 applied
ModeIn Office
CategoryMachine Learning
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