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Computer Vision Engineer

Infosys
Bengaluru, India
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  • Posted 3 days ago
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Job Description

  • 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.
  • Good knowledge on software configuration management systems
  • Strong business acumen, strategy and cross-industry thought leadership
  • Awareness of latest technologies and Industry trends
  • Logical thinking and problem solving skills along with an ability to collaborate
  • Two or three industry domain knowledge
  • Understanding of the financial processes for various types of projects and the various pricing models available
  • Client Interfacing skills
  • Knowledge of SDLC and agile methodologies
  • Project and Team management

More Info

Job Type:
Permanent Job
Industry:
Other
Function:
Computer Vision
Employment Type:
Full time

About Company

Infosys

Job ID: 151133711

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Last Updated: 14-07-2026 08:47:30 PM
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