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Computer Vision Engineer
Make models see — robustly, in production.
You build systems that classify, detect, segment, or generate images and video. The classic ML role that's far from dead — robotics, autonomy, AR/VR, medical imaging, content moderation all need you.
Skills profile
What hiring managers actually weigh.
Recommended paths
Take them in order. Each builds on the previous.
90-day roadmap
An honest, week-by-week plan. Adjust to your weekly time budget.
- 1
Foundations
~5 weeks- Linear algebra + autograd
- Train a CNN from scratch
- Read 5 CV classics (ResNet, ViT, YOLO)
- 2
Modern CV
~5 weeks- Fine-tune a vision transformer
- Object detection or segmentation project
- Data augmentation discipline
- 3
Production
~4 weeks- Optimize for latency (TensorRT / ONNX)
- Edge or cloud deploy
- Monitor for drift
Certifications worth taking
Practice & certify on CertQuests after completing the course.
Career outcomes
Realistic next steps after completing the roadmap.
- Robotics, AR/VR, autonomy, medical imaging roles
- Strong PhD pipeline if research-leaning
- Adjacent to ML Engineer