Computer Vision Engineer

This role is for one of Weekday’s clients
Salary range: Rs 1000000 - Rs 1500000 (ie INR 10-15 LPA)
Min Experience: 5 years
Location: Bengaluru
JobType: full-time

We are seeking a highly skilled and experienced Computer Vision Engineer to join our growing AI team. This role is ideal for someone with strong expertise in deep learning and a solid background in real-time video analytics, model deployment, and computer vision applications. You’ll be responsible for developing scalable computer vision pipelines and deploying them across cloud and edge environments, helping build intelligent visual systems that solve real-world problems.

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