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Physics Wallah logo — Physics Wallah Computer Vision Engineer Intern in Gurugram, Haryana
Physics Wallah VerifiedActively Hiring

Computer Vision Engineer Intern

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Location

Gurugram, Haryana

Work Mode

Hybrid

Duration

3 months

Stipend

₹41,000/mo

Start Date

Immediate / Rolling

Openings

3 positions

Type

Full-time

Category

AI & Machine Learning

Apply Now — ₹41,000/moApply on Company Website ↗

About the Internship

Join Physics Wallah in Gurugram as a Computer Vision Engineer Intern. This entry-level internship is designed for students and recent graduates who learn best by building, shipping and getting real feedback on computer vision and visual perception work. About the role As a Computer Vision Engineer…

About Physics Wallah

Physics Wallah offers a mentor-led Computer Vision Engineer Intern in Gurugram with live project work in ai & machine learning, a stipend of ₹41,000/month and a Pre-Placement Offer opportunity for strong performers.
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Gurugram, HaryanaVerified employer3 openings
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Skills Required

OpenCVConvolutional Neural Networks (CNNs)Image ProcessingYOLOEdge AI DeploymentPyTorchData Annotation & AugmentationPythonModel QuantisationCamera Calibration

Who Can Apply

  • Final-year students and recent graduates from B.E./B.Tech (CSE/ECE/EEE), M.Tech, MCA or M.Sc (CS / Electronics) who are based in or willing to work from Gurugram. You should be keen to learn OpenCV, Convolutional Neural Networks (CNNs), Image Processing 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. 2Technical interview on fundamentals and your projects
41,000/month

Stipend · 3 months

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Openings3 positions
Applicants0 applied
ModeHybrid
CategoryAI & Machine Learning
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