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Walk-in || Ai Ml Engineer

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Onsite

Walk-in || Ai Ml Engineer

e con Systems

Walk-in || Ai Ml Engineer

Skills

Deep LearningPythonPyTorchTensorFlowMachine Learning

17 days ago

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Important information


Contract type:

Permanent

Location:

Chennai, Tamil Nadu, India

Work mode:

Onsite

Published on:

6 October 2026

What they need


Inter Responsibilities:

  • Algorithm Development: Design, implement, and optimize computer vision and deep learning algorithms for object detection, segmentation, 3D reconstruction, OCR, anomaly detection, and pose estimation
  • End-to-End Pipeline Ownership: Develop and maintain robust vision pipelines, encompassing data ingestion, preprocessing, inference, post-processing, and system integration
  • Model Lifecycle Management: Train, fine-tune, evaluate, and deploy deep learning models (CNNs, Transformers, etc.) using frameworks like PyTorch, TensorFlow.
  • Performance Optimization: Optimize models for edge deployment using techniques such as quantization, pruning, and leveraging inference engines like TensorRT, ONNX, or OpenVINO to meet strict latency and power constraints
  • Embedded Integration: Collaborate with embedded engineers to port and optimize vision software for various hardware platforms (SoCs, GPUs, NPUs)
  • Research & Innovation: Stay current with the latest research in computer vision and machine learning, rapidly prototyping new techniques to enhance our capabilities
  • Software Engineering Best Practices: Write clean, documented, and maintainable code, and actively contribute to internal libraries, tools, and code reviews

Essential Skills

  • Bachelors/masters in computer science, Electrical Engineering, Robotics, or a related field
  • Industry experience in computer vision or machine learning
  • Strong programming proficiency in Python,C++ and OpenCV.
  • Deep, practical experience with at least one major deep learning framework (PyTorch is strongly preferred)
  • A proven track record of deploying real-time computer vision systems into a production environment
  • Experience deploying models on edge or embedded devices is a strong advantage.

Interested candidate please share your updated resume to the email id: [email protected]

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