SDE-; Computer Vision Engineer

Responsibilities

• Solve real-world Computer Vision problems using cutting‑edge techniques.
• Design and implement robust, industry‑grade algorithms
  .
• Utilize OpenCV
  , Python
  , and deep learning frameworks for model training.
• Work with deep learning libraries such as Keras
  , Tensor Flow
  , and Py Torch .
• Develop integrations with internal and external microservices
  .
• Implement deployment practices using Docker
  , Kubernetes
  , and model compression techniques.
• Research the latest technologies and develop proof of concepts (POCs).
• Build and train state‑of‑the‑art deep learning models for:
  • Object Detection (
    Mandatory
    )
  • Segmentation
  • Classification
  • Object Tracking
  • Visual Style Transfer
  • Generative Adversarial Networks (GANs)
• Collaborate with researchers and engineers to develop and deploy Computer Vision solutions.
• Plan and execute Computer Vision research projects
  , defining scope, objectives, and deliverables.
• Provide specialized technical and scientific research support for ongoing and new AI initiatives.

• C++ (Mandatory)
• Python (Mandatory)
• Image Processing (Mandatory)
• Computer Vision (Mandatory)
• Deep Learning (Mandatory)
• Object Detection
• Machine Learning Pattern Recognition
• Artificial Intelligence (AI)
• Data Science
• Generative Adversarial Networks (GANs)
• Flask
• SQL