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ReNew logo — ReNew Edge ML & Model Optimisation Intern in Nagpur, Maharashtra
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Edge ML & Model Optimisation Intern

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Location

Nagpur, Maharashtra

Work Mode

Hybrid

Duration

6 months

Stipend

₹27,000/mo

Start Date

Immediate / Rolling

Openings

15 positions

Type

Full-time

Category

Machine Learning

Apply Now — ₹27,000/moApply on Company Website ↗

About the Internship

Join ReNew in Nagpur as an Edge ML & Model Optimisation Intern. This entry-level internship is designed for students and recent graduates who learn best by building, shipping and getting real feedback on model compression and edge deployment work. About the role As an Edge ML & Model Optimisation…

About ReNew

ReNew offers a mentor-led Edge ML & Model Optimisation Intern in Nagpur with live project work in machine learning, a stipend of ₹27,000/month and a Pre-Placement Offer opportunity for strong performers.
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Nagpur, MaharashtraVerified employer15 openings
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Skills Required

Model QuantisationModel PruningTensorFlow Lite / ONNXPythonC/C++ BasicsEmbedded DeploymentLatency ProfilingKnowledge DistillationBenchmarkingHardware Constraints

Who Can Apply

  • Final-year students and recent graduates from B.E./B.Tech (CSE/ECE/EEE), M.Tech, MCA or M.Sc (Computer Science / Electronics) who are based in or willing to work from Nagpur. You should be keen to learn Model Quantisation, Model Pruning, TensorFlow Lite / ONNX 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

2 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
27,000/month

Stipend · 6 months

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Openings15 positions
Applicants0 applied
ModeHybrid
CategoryMachine Learning
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