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Computer Vision Engineer/ Lead

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Hybrid

Computer Vision Engineer/ Lead

Infosys

Computer Vision Engineer/ Lead

Skills

SQL QueriesDeep LearningDockerPythonPyTorchTensorFlowNeo4jData AnalysisMachine LearningAnsibleKubernetesTerraform

17 days ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Hybrid

Published on:

5 October 2026

What they need


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.

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