Job

Key responsibilities:

• Design, develop and implement computer vision algorithms to analyze and interpret video content.


• Large-scale video dataset creation (i.e. defining the dataset statistics) to build accurate, scalable video analytics solutions.


• Pose estimation from videos


• Integrate video analytics solutions into production environments. 


• Stay up-to-date with advancements in computer vision and video analytics technologies.

• Bachelor’s or Master’s degree in Computer Science, Computer Vision, Machine Learning, or a related field.


• 2+ years of experience in computer vision and video analytics.


• Strong proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch).


• Hands-on experience with OpenCV, video processing libraries, and deep learning architectures for vision tasks - CNNs and Transformers.


• Ability to implement state-of-the-art deep learning architectures as outlined in research papers


• Familiarity with deploying models on cloud platforms like AWS, Google Cloud, or Azure. Preferred Qualifications


• Experience with real-time video processing and object detection/recognition.


• Background in optimizing ML models for speed and accuracy in video applications and different hardware platforms.


• Familiarity with Docker, Git, ML Tracking/Visualization tools like Neptune.ai or Tensor board


• Experience in the conversion of models to formats that are compatible with mobiles.