AI Expert

6 days ago

Chennai, Tamil Nadu, India beBeeMachine Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
Job Title: Edge AI ArchitectWe're seeking a seasoned Edge AI Architect with expertise in building and deploying ML models optimized for edge devices.This role is ideal for someone passionate about pushing the boundaries of AI on resource-constrained hardware, across domains such as computer vision, audio analytics, and sensor-based signal processing.Key Responsibilities
  • 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.
Qualifications
  • Masters degree (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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