FINN

Edge AI Developer Intern

InternshipIn OfficeLudhiana, Punjab6 months25K/mo3 openingsImmediate / Rolling

About this internship

Join FINN in Ludhiana as an Edge AI Developer Intern. This entry-level internship is designed for students and recent graduates who learn best by building, shipping and getting real feedback on edge AI and on-device inference work. About the role As an Edge AI Developer Intern at FINN, your core…

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Skills you'll use

TensorRTTinyMLOpenVINOModel QuantisationEmbedded Hardware DeploymentC / C++PythonModel Pruning & DistillationLatency & Power ProfilingONNX Runtime

What you'll do

Work on squeezing models onto constrained hardware without losing accuracy alongside the core team
Apply TensorRT, TinyML, OpenVINO, Model Quantisation 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 (CSE/ECE/EEE), M.Tech or M.Sc (Electronics / CS) — 2026 freshers & final-year students welcome
Working knowledge of TensorRT, TinyML, OpenVINO (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 Ludhiana, Punjab

Perks & benefits

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:

1Application screening & resume shortlisting by the talent team
2Online aptitude / domain assessment

About FINN

FINN operates in the car subscription & mobility sector and has an active presence in Ludhiana. 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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