Physical AI Model Optimization Engineer - Qualcomm Advanced Robotics

Execute hardware-aware graph transformations and operator adjustments using QC-provided graph tools and compilers.

Validate accuracy, stability, and runtime behavior of quantized and optimized models on real robotic hardware.

Work closely with platform and robotics engineering teams to integrate optimized models into production systems.

Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

OR Master's degree in Computer Science, Engineering, Information Systems, or related field and 3+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

OR PhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

3+ years of experience in embedded or on-device AI, model optimization, or performance engineering.

Strong hands-on experience applying quantization (PTQ/QAT), pruning, compression, mixed-precision tuning, and model transformation techniques.

Proficiency with PyTorch (preferred), including model graph manipulation, tracing, and conversion workflows.

Understanding of the numerical behavior and accuracy trade-offs of low-precision AI.

Ability to diagnose and address performance bottlenecks in compute, memory, and bandwidth.

Experience deploying AI models to embedded or heterogeneous compute systems.

Robotics domain experience, especially with real-time constraints.

Familiarity with large multimodal or transformer-based architectures.

C++ skills for minor kernel-level tweaks or integration fixes.