Computer Vision Architect / Lead Engineer

Infosys; Bengaluru; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Infosys in Bengaluru is seeking a skilled deep learning engineer to design, train, and optimize CV models for object detection, recognition, and segmentation. You will manage real-time pipelines across many camera feeds, applying advanced techniques and state-of-the-art frameworks.

Responsibilities include fine-tuning CNNs and Vision Transformers with TensorFlow, PyTorch, and ONNX, plus deploying inference setups with NVIDIA tools and managing data processing for latency-sensitive tasks.

Qualifications

• Strong experience in designing, training, and optimizing deep learning models for computer vision tasks.
• Experience leading real-time video analytics across 100+ streams.
• Proficient with CNNs, Vision Transformers, and model fine-tuning using TensorFlow or PyTorch.

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.

Skills

Python

SQL

NoSQL

Graph DBs

Docker

Kubernetes

TensorFlow

PyTorch

ONNX

Education

Bachelor of Engineering

Bachelor Of Technology

Bachelor Of Science

Master Of Technology

Master Of Engineering

Tools

Docker

Kubernetes

Terraform

Ansible

Neo4j

Job description

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