Job Requirements
- Design and develop AI/ML-based applications with a focus on deployment on embedded hardware platforms (e.g., Renesas RZ/V2H, NVIDIA Jetson, STM32, etc.)
- Port and optimize AI models for real-time performance on resource-constrained embedded systems
- Perform model quantization, pruning, and conversion (e.g., ONNX, TensorRT, TVM, TFLite, DRP-AI) for deployment
- End-to-end AI model lifecycle development including data preparation, training, validation, and inference optimization
- Customize and adapt AI network architectures for specific edge AI use cases (e.g., object detection, classification, audio detection)
- Data Preparation & Preprocessing: Collect, organize, and preprocess audio/image datasets.
- Minimum 5 years of experience in AI/ML application development.
- Strong Python programming skills, including AI frameworks such as PyTorch, TensorFlow, Keras.
- Solid experience in developing deep learning-based solutions for Computer Vision, Imaging and Audio.
- Deep understanding of DL architectures like CNN, FCN and their application to visual tasks.
- Experience in model optimization techniques such as quantization, pruning, layer fusion, and INT8 calibration for edge inference.
- Hands-on experience in deploying AI models on embedded platforms.
- Proficiency in tools such as OpenCV, ONNX, TVM, TFLite, or custom inference engines.
- Understanding of system constraints like memory, compute, and power on edge devices.
- Exposure to real-time audio processing, video processing and robotics.
Salary
Hourly based
Location
KL , India KL, India
Job Overview
Location
KL , India KL, India
