Tools-ONNX/TF and TFLITE converters- Engineer, Staff/Manager

Qualcomm is seeking a Staff/Manager level Engineer to join their growing team focused on advancing state-of-the-art in Machine Learning. This role is centered around the development of tools for ONNX/TF and TFLITE converters, working with Qualcomm's extensive heterogeneous computing capabilities to enable neural network inference on-device.

The position offers an opportunity to work on cutting-edge ML solutions that directly impact billions of devices worldwide. You'll be part of a team that develops and commercializes critical ML infrastructure like the Snapdragon Neural Processing Engine (SNPE) and AI Model Efficiency Toolkit (AIMET).

Key responsibilities include designing and maintaining large AI software stacks, working with various deep learning frameworks, and optimizing neural networks for embedded systems. The role requires strong expertise in deep learning, proficiency in Python and C++, and experience with major ML frameworks like TensorFlow, ONNX, and PyTorch.

As a Staff Engineer at Qualcomm, you'll collaborate with a globally diverse team, working on solutions that push the boundaries of what's possible in on-device AI. The position offers comprehensive benefits including world-class health coverage, financial planning support, and continuous learning opportunities.

This is an excellent opportunity for experienced ML engineers who want to work on challenging problems in embedded AI, with direct impact on next-generation mobile devices and IoT systems. The role combines deep technical work with leadership opportunities, making it ideal for those looking to advance their careers in ML systems engineering.