Senior Machine Learning Engineer (Edge AI)

5 - 12 years

10 - 14 Lacs

chennai

Posted:3 weeks ago| Platform: Naukri logo

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Skills Required

training deep learning computer vision analytical machine learning signal processing data quality continuous improvement python embedded software

Work Mode

Work from Office

Job Type

Full Time

Job Description

  • Design, train, and optimize deep learning models for edge AI use cases:
  • Computer vision (e.g., object detection, image classification, segmentation)
  • Audio/speech processing (e.g., wake word detection, denoising)
  • Signal processing across multimodal sensor data
  • Develop scalable and efficient model training and evaluation pipelines.
  • Quantize, prune, and compress models for real-time inference on NPUs, DSPs, and microcontrollers.
  • Conduct applied research and benchmark new model architectures or techniques for edge deployment.
  • Prepare and curate training/validation datasets using best practices for data quality and balance.
  • Collaborate with embedded software engineers to integrate models into edge production environments.
  • Monitor model performance, perform error analysis, and iterate for continuous improvement.
  • Document model architectures, assumptions, and deployment requirements for stakeholders.

    Requirements
    • Masterdegree (or equivalent experience) in Computer Science, Machine Learning, or a related discipline.
    • 5+ years of hands-on experience in developing, optimizing, and deploying ML models in production.
    • Strong proficiency in Python and ML frameworks such as TensorFlow, PyTorch, ONNX , and tools like OpenCV , Ultralytics , or equivalent.
    • Demonstrated experience with edge inference optimization :
    • Model quantization and compression
    • Deployment on NPUs , DSPs , or microcontrollers
    • Familiarity with ARM Ethos-U/Vela , TensorRT , TFLite , or similar edge AI compilers is a strong plus.
    • Solid understanding of signal processing for image, audio, and other sensor modalities.
    • Experience with cloud-based training pipelines (AWS, GCP, or Azure) is a plus.
    • Strong analytical and problem-solving skills, with a track record of innovation.
    • Excellent communication and documentation skills.

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