#Agentic AI Windows Power and Thermal Engineer at Qualcomm
San Diego, CA
$94,200–$141,200from the description
Jul 13, 2026
San Diego, CA
Jul 21, 2026
What this job asks for AI summary
A software engineering role focused on power and thermal management across Qualcomm's chipset platforms, including mobile, automotive, and AR/VR. Day-to-day work involves system-level analysis of power and thermal use cases, building AI/ML-driven automation pipelines to process telemetry data, and collaborating with hardware, architecture, and performance teams to develop optimized power management solutions. Suits engineers with a background in SoC systems, embedded software, and machine learning infrastructure.
Mid level · National · Bachelor's required · Full-time
“or” means any one of them counts — you don't need all of them.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
What the occupation pays Median $138,970 (middle half $107,524–$175,762). This posting is about at that midpoint.
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (7)
No work location or CBSA is specified in the posting; the pay range ($94,200–$141,200/year) is consistent with Qualcomm's San Diego, CA headquarters but cannot be confirmed from the text alone.
The role is explicitly ineligible for Qualcomm immigration sponsorship.
The posting lists only a Bachelor's degree in Engineering, Information Systems, Computer Science, or a related field as a hard minimum requirement; all technical skills appear exclusively under 'Preferred Qualifications' and are therefore not hard gates.
The role blends embedded/power-thermal software engineering with AI/ML infrastructure work (neural network design, training, deployment, telemetry pipeline automation), making the primary SOC classification a genuine judgment call between Software Developers (15-1252) and Data Scientists (15-2051); Software Developers was chosen because the core deliverables are software products and automation tooling rather than modeling/research.
No overall years-of-experience requirement is stated.
Neural network architecture types (CNNs, LLMs, Transformers) are listed together as interchangeable examples of model expertise; captured as a single preferred skill with alternatives.
Ignored 5 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): AI/ML model development, data pipeline management, infrastructure automation, SoC power management, microprocessor architecture.
Read the full posting
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