Computer Vision Engineer

Requirements

Computer Vision Engineer

Key Responsibilities:

• Model Development & Training: Design, train, and optimize deep learning models for object detection, segmentation, and tracking using frameworks like YOLO, UNet, Mask R-CNN, and Deep SORT.
• Computer Vision Applications: Build robust pipelines for computer vision applications including image classification, real-time object tracking, and video analytics using OpenCV, NumPy, and TensorFlow/PyTorch.
• Deployment & Optimization: Deploy trained models on Linux-based GPU systems and edge devices (e.g., Jetson Nano, Google Coral), ensuring low-latency performance and efficient hardware utilization.
• Real-Time Inference: Implement and optimize real-time inference systems, ensuring minimal delay in video processing pipelines.
• Model Management: Utilize tools like Docker, Git, and MLflow (or similar) for version control, environment management, and model lifecycle tracking.
• Collaboration & Documentation: Work cross-functionally with hardware, backend, and software teams. Document designs, architectures, and research findings to ensure reproducibility and scalability.
  

Technical Expertise Required:

• Languages & Libraries: Advanced proficiency in Python and solid experience with OpenCV, NumPy, and other image processing libraries.
• Deep Learning Frameworks: Hands-on experience with TensorFlow, PyTorch, and integration with model training pipelines.
• Computer Vision Models:
• Object Detection: YOLO (all versions)
• Segmentation: UNet, Mask R-CNN
• Tracking: Deep SORT or similar
• Deployment Skills:
• Real-time video analytics implementation and optimization
• Experience with Docker for containerization
• Version control using Git
• Model tracking using MLflow or comparable tools
• Platform Experience: Proven experience in deploying models on Linux-based GPU environments and edge devices (e.g., NVIDIA Jetson family, Coral TPU).
  

Professional & Educational Requirements:

• Education: B.E./B.Tech/M.Tech in Computer Science, Electrical Engineering, or related discipline.
• Experience:
• Minimum 5 years of industry experience in AI/ML with a strong focus on computer vision and system-level design.
• Proven portfolio of production-level projects in image/video processing or real-time systems.
  

Preferred Qualities:

• Strong problem-solving and debugging skills
• Excellent communication and teamwork capabilities
• A passion for building smart, scalable vision systems
• A proactive and independent approach to research and implementation