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Fyle logo — Fyle ML Optimisation & Operations Research Intern in Kolkata, West Bengal
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ML Optimisation & Operations Research Intern

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Location

Kolkata, West Bengal

Work Mode

Hybrid

Duration

2 months

Stipend

₹18,000/mo

Start Date

Immediate / Rolling

Openings

5 positions

Type

Full-time

Category

Machine Learning

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About the Internship

Join Fyle in Kolkata as a ML Optimisation & Operations Research Intern. This entry-level internship is designed for students and recent graduates who learn best by building, shipping and getting real feedback on optimisation and operations research work. About the role As a ML Optimisation &…

About Fyle

Fyle offers a mentor-led ML Optimisation & Operations Research Intern in Kolkata with live project work in machine learning, a stipend of ₹18,000/month and a Pre-Placement Offer opportunity for strong performers.
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Kolkata, West BengalVerified employer5 openings
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Skills Required

Operations ResearchLinear & Integer ProgrammingPythonOR-Tools / PuLPHeuristics & MetaheuristicsConstraint ModellingSimulationData AnalysisCost ModellingScenario Testing

Who Can Apply

  • Final-year students and recent graduates from B.E./B.Tech (Industrial / Mechanical / CSE), M.Tech, M.Sc (Mathematics / Statistics) or MBA (Operations) who are based in or willing to work from Kolkata. You should be keen to learn Operations Research, Linear & Integer Programming, 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

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

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
18,000/month

Stipend · 2 months

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Openings5 positions
Applicants0 applied
ModeHybrid
CategoryMachine Learning
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