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Role Overview

Join our AI Research & Development team to push the boundaries of embedded artificial intelligence. As an AI/ML Engineer, you will research, train, and quantize deep learning models (TinyML) to execute inference on ultra-low-power edge silicon with sub-millisecond latencies.

Key Responsibilities

• Research, train, and fine-tune state-of-the-art computer vision, NLP, and sensor-fusion machine learning models.
• Optimize and quantize models using TensorRT, ONNX Runtime, OpenVINO, and TensorFlow Lite for edge deployment.
• Develop efficient data pipelines for model training, dataset curation, and continuous model performance benchmarking.
• Collaborate with firmware and VLSI teams to benchmark neural network execution against hardware NPU targets.

Qualifications & Requirements

• BS/MS/PhD in Computer Science, Artificial Intelligence, Data Science, or related field.
• 3+ years of experience developing and deploying production machine learning models.
• Proficiency in Python, PyTorch / TensorFlow, and deep learning optimization techniques (quantization, pruning).
• Demonstrated experience with edge AI deployments and embedded inference acceleration.