Careers
Quick summary
- Work type
- On-site
- Location
- San Diego, CA
- Posted
- 43 days ago
- Nearby
- 99+ roles within 25 mi
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Salary context
How this pay compares to similar roles
This listing doesn't post a salary. Most similar roles pay $152,075–$208,800.
Based on 239 similar postings.
Employer
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.
Skills
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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