60 Qualcomm Professional Engineer Jobs Hiring Near You

Company:
Qualcomm Technologies, Inc.
Job Area:
Engineering Group, Engineering Group > Machine Learning Engineering
General Summary:
About Qualcomm Robotics
Qualcomm Advanced Robotics Team is building the AI first stack and platform for the next generation general purpose robots - from AMRs and cobots to emerging humanoids by pairing heterogeneous compute (CPU/GPU/DSP/NPU) with a full Robotics SDK and developer tooling for manipulation, perception, navigation, and fleet workflows. We are leveraging our success in automated driving product portfolio, advanced AI end to end development and tools, and safety architecture to accelerate the growth in this emerging market.
About the Role
We are seeking a Physical AI Model Optimization Engineer to help bring cutting-edge robotic AI models onto Qualcomm Dragonwing chipsets using Qualcomm's internal deployment and optimization toolchains. This role is highly execution-focused and centers on applying existing Qualcomm tools, workflows, and compilers to onboard, optimize, validate, and deploy advanced AI models for real-time robotic systems.
A key responsibility of this team is creating and maintaining a curated library of robotics-focused AI models that are pre-optimized for deployment on Qualcomm chips. These models-spanning perception, control, VLA, and multimodal reasoning-will be packaged, validated, and made available for customers as high-performance, deploy-ready components that accelerate their development cycles.
You'll work hands-on with next-generation models transforming research architectures into reliable, hardware-efficient implementations. You will work directly with Qualcomm's AI Stack and contribute targeted fixes, enhancements, or feature requests that improve Qualcomm's internal pipelines for robotics-focused usecases.
Your work will directly impact real robots-and the teams building them.
What you'll do

• Use Qualcomm's internal AI toolchains to onboard, convert, and optimize large-scale research models for Dragonwing deployment.
• Apply Qualcomm-supported quantization, compression, and mixed-precision workflows to meet latency, memory, and power constraints.
• Execute hardware-aware graph transformations and operator adjustments using QC-provided graph tools and compilers.
• Profile model performance across heterogeneous compute (NPU/DSP/GPU/CPU) using Qualcomm profiling utilities and diagnose optimization opportunities.
• Validate accuracy, stability, and runtime behavior of quantized and optimized models on real robotic hardware.
• Build automation, scripts, and reproducible processes around Qualcomm's toolchains to accelerate onboarding throughput.
• Provide bug reports, patches, or minor contributions back to Qualcomm tools where needed to support model deployment, but not as a primary responsibility.
• Work closely with platform and robotics engineering teams to integrate optimized models into production systems.

Why Qualcomm

• Gain direct access to state-of-the-art robotic AI models and run them on advanced heterogeneous compute.
• Work at the intersection of embedded AI, robotics, and high-performance model optimization.
• Collaborate with teams building Qualcomm's inference engines, compilers, and silicon.
• Ship improvements that immediately affect real robots across industries.

Minimum Qualifications:
• 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.
Preferred Qualifications:

• 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.
• Experience using vendor-specific AI optimization pipelines (Qualcomm preferred; others such as TensorRT, TVM, XLA, or ONNX Runtime are also relevant).
• 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.
• Experience with the Qualcomm AI Stack, NPU/DSP optimization, or related chipset-specific AI workflows.
• 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.

Why Join Us?

• Shape the core platform that powers intelligent, safe, and scalable robotic operations.
• Work with some of the most advanced robotic AI models on the planet.
• Influence the optimization and deployment pipeline for next-generation robotic intelligence.
• Competitive compensation, deep technical growth, and the opportunity to shape the future of on-device AI.

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Pay range and Other Compensation & Benefits:
$158,400.00 - $237,600.00
The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Even more importantly, please note that salary is only one component of total compensation at Qualcomm. We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus). In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to offer - and you can review more details about our US benefits at this link.
If you would like more information about this role, please contact Qualcomm Careers.