Location
Mumbai, Maharashtra
Work Mode
Work from Home
Duration
3 months
Stipend
₹35,000/mo
Start Date
Immediate / Rolling
Openings
2 positions
Type
Full-time
Category
Machine Learning
About the Internship
Malabar Gold & Diamonds has an open Computer Vision Engineer Intern position in Mumbai for motivated freshers and final-year students. You will work on live computer vision projects and finish with something you can genuinely talk about in interviews.
About the role
As a Computer Vision Engineer…
About Malabar Gold & Diamonds
Malabar Gold & Diamonds offers a mentor-led Computer Vision Engineer Intern in Mumbai with live project work in machine learning, a stipend of ₹35,000/month and a Pre-Placement Offer opportunity for strong performers.
See all Malabar Gold & Diamondsinternships →Mumbai, MaharashtraVerified employer2 openings
Apply to Malabar Gold & Diamonds →Skills Required
Computer VisionOpenCVPyTorchObject Detection (YOLO)Image SegmentationPythonCNN ArchitecturesData AugmentationAnnotation ToolsModel Evaluation (mAP / IoU)
Who Can Apply
- Final-year students and recent graduates from B.E./B.Tech (CSE/ECE/EEE/AI-ML), M.Tech, MCA or M.Sc (Computer Science) who are based in or willing to work from Mumbai. You should be keen to learn Computer Vision, OpenCV, PyTorch 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
Live project experienceExposure to professional tools and workflowsPre-Placement Offer (PPO) opportunityFlexible working hoursNetworking with senior professionals
Interview & Selection Process
4 rounds — typical selection flow for this role:
- 1Application screening & resume shortlisting by the talent team
- 2Practical assignment or case study with a short walkthrough
- 3Discussion with the hiring manager on the role and your fit
- 4HR discussion — stipend, start date, expectations and offer
₹35,000/month
Stipend · 3 months
Openings2 positions
Applicants2 applied
ModeWork from Home
CategoryMachine Learning
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