Computer Vision Architect/ Lead/ Engineer

Educational Requirements

Bachelor of Engineering,Bachelor Of Technology,Bachelor Of Science,Bachelor Of Comp. Applications,Master Of Technology,Master Of Engineering,Master Of Science,Master Of Comp. Applications

Service Line

Engineering Services

Responsibilities

• 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.

Preferred Skills:

• Technology->AI-AI Hyperscalers->Azure Agentic AI Services->Computer Vision with Azure
• Technology->AI-Data science->Computer Vision
• Technology->AI-AI Engineering->AI/ML Solution Architecture and Design
• Technology->AI-AI Engineering->MLOps->mlflow

Generic Skills:

• Technology->AI-Data science->PYTHON