Physical AI Model Optimization Lead - Qualcomm Advanced Robotics Team
Company: Qualcomm
Location: San Diego
Posted on: April 7, 2026
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Job Description:
Company: Qualcomm Technologies, Inc. Job Area: Engineering
Group, Engineering Group > Machine Learning Engineering General
Summary: Hiring in San Diego and Santa Clara About Qualcomm
Robotics Qualcomm’s Advanced Robotics Team is building an AI?first
stack and platform for the next generation of 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. The team leverages Qualcomm’s success in automated
driving, advanced end?to?end AI development, and safety
architecture to accelerate growth in this emerging market. Role
Overview The Physical AI Model Optimization Lead will drive the
technical execution of advanced robotic AI model deployment on
Qualcomm chipsets. This is a deeply technical, hands?on role
focused on quantization, compression, optimization, mixed?precision
tuning, and hardware?aware graph transformations using Qualcomm’s
internal toolchains. A key responsibility of this role 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. This role provides exposure to
industry?leading robotics?centric AI models, including
next?generation vision?language?action (VLA) architectures and
complex multimodal transformers and reasoning models, with
responsibility for taking models from research?grade to highly
optimized real?time deployment on heterogeneous compute. Your work
will directly impact real robots—and the teams building them. 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 in the world. - Influence the
optimization and deployment pipeline for next?generation robotic
intelligence. - Access competitive compensation, deep technical
growth, and opportunities to shape the future of on?device AI.
Minimum Qualifications: • Bachelor's degree in Computer Science,
Engineering, Information Systems, or related field and 6 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 5 years of
Hardware Engineering, Software Engineering, Systems Engineering, or
related work experience. OR PhD in Computer Science, Engineering,
Information Systems, or related field and 4 years of Hardware
Engineering, Software Engineering, Systems Engineering, or related
work experience. Preferred Qualifications: - MS in Computer
Science, Electrical Engineering, Robotics, or a related field; PhD
a plus. - 5 years of experience in embedded/on?device AI, model
optimization, or performance engineering. - Deep technical
expertise in: - Mixed?precision quantization (INT8/FP16/FP8) - QDQ
graph?based quantization flows - PTQ and QAT workflows - Model
compression techniques (pruning, distillation, low?rank methods) -
Strong experience with ONNX and PyTorch or TensorFlow model export
and graph manipulation. - Hands?on profiling experience on edge
devices, custom SoCs, or heterogeneous compute targets. -
Experience with Qualcomm toolchains: AI Hub Workbench, AIMET, QNN,
QGenie, or similar. - Background optimizing transformer?based
perception, VLMs, and VLA architectures. - Understanding of
heterogeneous compute system design and operator scheduling. -
Direct experience supporting customers or partners in model
deployment and performance tuning. Responsibilities - Execute
end?to?end model optimization, including graph rewrites, operator
fusion, and hardware?specific transformations. - Apply
mixed?precision quantization and QDQ workflows (PTQ/QAT) for
high?performance deployment. - Implement compression techniques
such as pruning, distillation, and low?rank factorization. - Debug
accuracy issues using fine?grained tensor comparisons during
quantization and conversion. - Use Qualcomm tools (AI Workbench,
AIMET, QNN, QGenie, profilers) to convert, validate, and optimize
models. - Map and tune models across heterogeneous compute
(DSP/NPU/GPU), including operator placement and kernel selection. -
Perform detailed performance profiling and analyze memory, tiling,
and scheduling behavior. - Collaborate with internal teams and
external customers to integrate, tune, and validate models on
Dragonwing hardware. How You’ll Lead - Set the technical bar for
optimization of physical AI models. - Own optimization workflows
from initial model drop ? compression ? mixed?precision/QDQ
quantization ? conversion ? on?device profiling ? final tuned
deployment. - Work closely with Qualcomm’s existing tools and
teams—AI Hub Workbench, QNN, AIMET, QGenie, compiler, and robotics
AI. - Serve as the technical authority on quantization correctness,
mixed?precision design, and hardware?aware optimization for
physical AI. - Drive improvements in internal tools and processes
through hands?on experiments and data?driven reporting. 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 impact real robots across industries. Qualcomm is an
equal opportunity employer. If you are an individual with a
disability and need an accommodation during the application/hiring
process, rest assured that Qualcomm is committed to providing an
accessible process. You may e-mail
disability-accomodations@qualcomm.com or call Qualcomm's toll-free
number found here. Upon request, Qualcomm will provide reasonable
accommodations to support individuals with disabilities to be able
participate in the hiring process. Qualcomm is also committed to
making our workplace accessible for individuals with disabilities.
(Keep in mind that this email address is used to provide reasonable
accommodations for individuals with disabilities. We will not
respond here to requests for updates on applications or resume
inquiries). To all Staffing and Recruiting Agencies: Our Careers
Site is only for individuals seeking a job at Qualcomm. Staffing
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unsolicited resumes/applications. EEO Employer: Qualcomm is an
equal opportunity employer; all qualified applicants will receive
consideration for employment without regard to race, color,
religion, sex, sexual orientation, gender identity, national
origin, disability, Veteran status, or any other protected
classification. Qualcomm expects its employees to abide by all
applicable policies and procedures, including but not limited to
security and other requirements regarding protection of Company
confidential information and other confidential and/or proprietary
information, to the extent those requirements are permissible under
applicable law. Pay range and Other Compensation & Benefits:
$178,400.00 - $267,600.00 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.
Keywords: Qualcomm, Vista , Physical AI Model Optimization Lead - Qualcomm Advanced Robotics Team, Engineering , San Diego, California