- Design, train, and optimize deep learning models for computer vision tasks such as object detection, image recognition, segmentation, and video analytics.

- Lead large-scale real-time implementations involving 100+ video streams.

- Fine-tune models like CNNs and Vision Transformers using frameworks such as TensorFlow, PyTorch, and ONNX.

- Build and deploy inference pipelines using NVIDIA technologies including NGC models, TAO Toolkit, DeepStream Metropolis, and Triton Server.

- Apply pre- and post-processing techniques to enhance model performance and evaluation.

- Develop and implement multi-object tracking algorithms across multiple camera feeds., Perform camera calibration and extract regions of interest (ROI), action recognition using temporal analysis techniques.

- Develop models for feature extraction and come up with strategies for latent space analysis and manipulation of the data.

- Proficiency in writing complex SQL queries, familiarity with NoSQL or Graph Databases (Neo4j) is an advantage.

- Knowledge of infrastructure as code tools (e.g., Terraform, Ansible) is an advantage.

- Proficiency with containerization technologies (Docker) and orchestration tools (Kubernetes) is an advantage.

📌 Computer Vision Architect/ Lead/ Engineer (Bangalore East)
🏢 Infosys
📍 Bangalore East