Computer Vision Architect/ Lead

Infosys; Bengaluru; Vor Ort; INR 1.200.000 - 2.200.000; Vollzeit

Zusammenfassung

Infosys in Bengaluru is seeking a Computer Vision Engineer with hands-on experience in developing and deploying deep learning models for real-time image and video analytics.

You will work on CV/ML/DL model development, handle object and action recognition, and deploy edge-ready solutions using NVIDIA tech, MLOps, and containers.

Aufgaben

• Design, train, and optimize deep learning models for CV tasks including object detection, image recognition, segmentation, and video analytics.
• Lead large-scale real-time implementations involving 100+ video streams.
• Fine-tune CNNs and Vision Transformers using TensorFlow, PyTorch, and ONNX.
• Build and deploy inference pipelines with NVIDIA technologies such as NGC models, TAO Toolkit, DeepStream, and Triton Server.
• Apply pre- and post-processing techniques to enhance model performance and evaluation.
• Develop multi-object tracking across multiple camera feeds and perform ROI extraction.
• Develop models for feature extraction and latent space analysis.

Kenntnisse

Python

PyTorch

TensorFlow

CV/ML/DL model development

Object detection recognition

Action recognition

NVIDIA technologies

MLOps

Edge deployment

Ausbildung

Master Of Engineering

Master Of Technology

MCA

MSc

Bachelor of Engineering

Bachelor Of Technology

BCA

BSc

Jobbeschreibung

Job Description

We are seeking a highly skilled Computer Vision Engineer with hands‑on experience in developing and deploying deep learning models for real‑time image and video analytics. The ideal candidate will have a strong background in computer vision, deep learning frameworks, and edge deployment technologies.

Computer Vision Specialists with hands‑on experience in:

• Python, PyTorch, TensorFlow
• CV/ML/DL model development
• Object detection recognition, Action recognition
• NVIDIA technologies
• MLOps, Edge deployment

Roles 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.

Educational Requirement

Master Of Engineering,Master Of Technology,MCA,MSc,Bachelor of Engineering,Bachelor Of Technology,BCA,BSc

Preferred Skills

Technology->AI-AI Hyperscalers->Azure Agentic AI Services->Computer Vision with Azure,Technology->AI-Data science->Computer Vision->Object detection and Recognition,Technology->AI-Generative AI->Image Video processing,Technology->OpenSystem->Python - OpenSystem->Python

Service Line

Engineering Services