Senior AI Engineer building and deploying edge AI solutions that fuse machine learning with hardware systems, from data collection to model deployment on embedded platforms.
About the role
Key Responsibilities
Design, prototype, and assemble hardware setups including sensor arrays and embedded boards for edge AI experiments.
Collect, preprocess, and analyze sensor data to create robust training datasets.
Develop and train machine learning models using Python and TensorFlow/PyTorch, optimizing for low‑latency inference.
Implement model conversion, quantization, and deployment pipelines onto embedded devices (e.g., ARM Cortex, NVIDIA Jetson).
Collaborate with firmware and hardware teams to integrate AI modules into real‑world systems.
Validate performance, troubleshoot issues, and iterate on models and hardware configurations.
Requirements
5+ years of experience in AI/ML engineering with a focus on edge deployment.
Proficiency in Python, TensorFlow/PyTorch, and C/C++ for embedded development.
Hands‑on experience with sensor data acquisition, preprocessing, and feature extraction.
Strong understanding of embedded systems, real‑time constraints, and hardware‑software co‑design.
Excellent problem‑solving skills and ability to work cross‑functionally in a fast‑paced environment.