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Qualcomm

Quick summary

Work type
On-site
Location
San Diego, CA
Posted
43 days ago

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How this pay compares to similar roles

Similar $180k
$118k most similar roles pay here $247k

This listing doesn't post a salary. Most similar roles pay $152,075–$208,800.

Based on 239 similar postings.

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About Qualcomm

Qualcomm is a leading American semiconductor and telecommunications company based in San Diego, CA.

Qualcomm currently has 660 open roles on FindRole.

Listed pay typically runs $154,000–$231,000 across 429 roles with salary data.

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At a glance

TL;DR · Careers

As a Physical AI Model Optimization Engineer at Qualcomm, you will join a dedicated team focused on deploying cutting-edge robotic AI models onto Dragonwing chipsets. Your primary responsibilities include using Qualcomm’s internal toolchains to optimize large-scale research models for real-time deployment, applying quantization and compression techniques to meet hardware constraints, and validating optimized models on actual robotic systems. You will work closely with the Qualcomm AI Stack, contributing enhancements that improve model performance across heterogeneous compute environments. The role requires strong expertise in deep learning frameworks like PyTorch or TensorFlow, proficiency in Python, and familiarity with robotics systems such as ROS 2. This position offers a unique opportunity to collaborate on advanced robotic AI models that bridge research and real-world applications, impacting the development of intelligent robots globally.

What you'll do

  • Use Qualcomm’s internal toolchains to onboard and optimize large-scale research models for Dragonwing deployment.
  • Apply quantization, compression, and mixed-precision workflows to meet hardware constraints for latency, memory, and power.
  • Execute graph transformations using QC-provided tools and compilers to enhance model efficiency on heterogeneous compute.
  • Profile and validate optimized models’ performance and stability on real robotic hardware across different compute units.
  • Build automation scripts and reproducible processes around Qualcomm’s toolchains to accelerate the deployment of AI models.

What we're looking for

  • 3+ years experience in embedded or on-device AI model optimization.
  • Strong hands-on expertise with quantization, pruning, compression techniques.
  • Proficiency in PyTorch for model graph manipulation and conversion workflows.
  • Experience deploying AI models to heterogeneous compute systems like Qualcomm's.
  • Robotics domain knowledge, especially dealing with real-time constraints.

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