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Computer Vision Internship

Ship real detection and vision systems.

An 8–12 week paid internship where you work on real image and video pipelines — detection, OCR, video analytics — deployed to production, under a practicing computer vision engineer.

Move from training notebooks to a deployed vision system

This is the internship that follows our Computer Vision training — you're placed on a real vision project, working on detection, OCR, or video analytics tied to an actual manufacturing, security, or document-processing requirement.

You'll ramp up on the project's data and pipeline in week one, move into guided model and pipeline work, and by the second half of the internship, you'll be owning a vision feature end to end, from data through evaluation and deployment.

8–12 Weeks
Duration
Online & Offline
Format
Computer Vision
Track
Performance-based
Stipend
Online / Offline
Mode
8–12 Weeks
Duration
4–6 Interns
Cohort Size
Full-time, Weekdays
Schedule

What you'll work on

Real vision pipeline work, scoped to grow with your skill level.

Image Processing Pipeline Work

Build and refine preprocessing steps for a real image or video dataset.

Model Training & Evaluation

Train, evaluate, and tune a detection or classification model on real data.

Object Detection Features

Build or extend detection and localization features for a live project.

OCR & Document Pipelines

Work on structured data extraction from real scanned documents or images.

Code Review Participation

Have your pull requests reviewed, and review others', as part of the team's workflow.

Model Optimization & Deployment

Help optimize and deploy models to a real cloud or edge environment.

Technologies you'll work with

Python
Core Language
OpenCV
Image Processing
PyTorch / TensorFlow
Deep Learning
CNN Architectures
Model Design
Object Detection Models
Detection
OCR Engines
Text Recognition
Video Analytics
Real-time Processing
ONNX & Edge Deployment
Model Deployment

How the internship is structured

A four-phase structure that moves you from onboarding to owning a real vision feature.

01. Onboarding & Project Ramp-up

Week 1
  • Tooling and environment setup
  • Data and pipeline walkthrough
  • Meet your mentor and team
  • First small, guided task

02. Guided Model & Pipeline Work

Weeks 2–6
  • Paired work on real training and pipeline tickets
  • Daily standups and sprint planning
  • Code review on every pull request
  • Mid-internship progress check-in

03. Independent Feature Ownership

Weeks 7–10
  • Own a vision feature end-to-end with mentor support
  • Run model evaluation and benchmarking
  • Participate in deployment
  • Document your work for the team

04. Final Presentation & Evaluation

Weeks 11–12
  • Present your shipped work to the team
  • Mentor evaluation and written feedback
  • Certificate and LOR eligibility review
  • Full-time opportunity discussion, if applicable

The kind of work interns actually ship

Real examples of feature scope Computer Vision interns take on.

Defect Detection Model Tuning

Improved detection accuracy on a live manufacturing defect classification model.

CNNsOpenCVTransfer Learning

Attendance System Face Matching

Added a face-matching improvement to a live automated attendance system.

Object DetectionOpenCVPython

Invoice Field Extraction

Built a new field-extraction rule set for an OCR pipeline processing real invoices.

OCRPreprocessingPython

What makes this internship real

Real Datasets, Not Benchmarks

You work with messy, real-world image and video data, not clean benchmark datasets.

A Named Mentor

You're paired with one computer vision engineer for the full internship who reviews your work.

Deployment-focused Practice

You practice optimizing and shipping models, not just training them in a notebook.

Eligibility

Basic Python Knowledge

Comfortable reading and writing basic Python is expected.

OpenCV or PyTorch Exposure Helpful

Prior exposure to OpenCV, PyTorch, or our Computer Vision training program is a plus, but not mandatory.

Full-time Availability

Able to commit to a full-time, weekday schedule for the internship's duration.

A GitHub Profile

Any prior project work or coursework repos you can share with your application.

What you walk away with

Performance-based Stipend

A paid internship, with stipend tied to your track and prior experience.

Certificate of Completion

Awarded to every intern who completes the program's full evaluation.

Letter of Recommendation

Issued to strong performers based on their mentor's written evaluation.

A Real Shipped Portfolio

A deployed vision feature you can show and speak to in interviews.

Full-time Consideration

Top performers are considered first when Computer Vision Engineer roles open.

A Direct Mentor Reference

A working computer vision engineer who can speak to your work firsthand.

Why intern with YashOrbit

You Ship, Not Just Learn

Every intern's work goes into a real deployed vision feature, not a training notebook.

Mentors Who Are Still Building

You're reviewed by engineers actively shipping vision systems to clients.

A Clear Path to Full-time

Strong performance is the primary path to a full-time offer, evaluated transparently.

Frequently asked questions

Yes, this is a paid internship with a performance-based stipend, shared with you during the selection process.

Ready to intern on real Computer Vision work?

Apply for the Computer Vision internship and start shipping vision systems that actually go live.

Free consultation
Dedicated team
Agile methodology