- Strong experience in Computer Vision techniques such as object detection, image/video segmentation, and multi-object tracking.
- Expertise in deep learning models including VLMs, GANs, and CNN-based architectures for vision tasks.
- Hands-on experience with PyTorch / TensorFlow and Python.
- Experience working on Edge AI platforms (NVIDIA, Qualcomm, or similar edge devices).
- Exposure to synthetic data generation pipelines (custom or standard platforms).
Valuable-to-Have Skills:
- Knowledge of MLOps pipelines, model deployment, and monitoring
- Experience in model optimization and performance tuning
- Familiarity with cloud platforms or distributed training environments
Key Responsibilities:
- Design, develop, and deploy computer vision models for real-world applications
- Implement, train, and fine-tune deep learning models for vision-based tasks
- Develop and optimize synthetic data pipelines for training robustness
- Deploy AI models on edge devices ensuring performance and scalability
- Collaborate with cross-functional teams to integrate CV solutions into products
- Perform model evaluation, debugging, and performance optimization
- Contribute to MLOps workflows and automation pipelines