Senior Staff Engineer, Machine Learning Engineering ( On-device SW )

Qualcomm; San Diego (CA); On-site; USD 194,000 - 292,000; Full time

Job summary

Qualcomm AI Research seeks talented AI software engineers to enable AI on edge devices. You will join a high‑caliber team building GenAI solutions with model optimization tools for edge deployment, focusing on power, memory, and compute efficiency.

You will work across hardware, software, and systems to bring next‑gen AI capabilities to smartphones, autonomous vehicles, robotics, and IoT devices.

Qualifications

• Bachelor's degree with 6+ years of relevant work experience.
• Master's degree with 5+ years of relevant work experience.
• PhD with 4+ years of relevant work experience.

Responsibilities

• Develop end-to-end embedded AI software for training and fine-tuning models on Qualcomm hardware.
• Design and optimize ML/AI software stack, kernels, and runtime for power efficiency.
• Collaborate with AI Processor Hardware team on new ML operators and layers.
• Create debugging/profiling tools and SDKs for customer deployment.

Skills

ML frameworks (PyTorch)

Programming (Python)

Programming (C/C++)

Software design

Android programming

HW-aware optimization

Neural network training

Quantization

QNN SDK experience

Education

Bachelor's degree in CS/Engineering/IS

Master's degree in CS/Engineering/IS

PhD in CS/Engineering/IS

Tools

QNN SDK

Job description

Company

Qualcomm Technologies, Inc.

Job Area

Engineering Group, Engineering Group > Machine Learning Engineering

General Summary

Qualcomm AI Research is looking for talented AI software engineers to enable AI technologies on edge devices. This is your opportunity to join a high‑caliber team of engineers, building best‑in‑class GenAI solutions with model optimization tools to deploy state‑of‑the‑art models to edge devices with optimal power, memory, and computation use.

In this role, you will be part of a multi‑disciplinary team that has continually enabled first‑of‑its‑kind and competitive generative AI models on Qualcomm AI accelerator engines, such as the world’s first on device text‑to‑image generation with stable diffusion, and text‑to‑text with large language model on device. You will collaborate in a cross‑functional environment spanning hardware, software and systems and see your design in action on industry‑leading chips embedded in the next generation of intelligent devices, such as smartphones, autonomous vehicles, robotics, and IOT devices.

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.

Responsibility

• Development of end-to-end embedded AI software to train and finetune neural network models on Qualcomm leading edge hardware with optimal resources.


• Design and enhance the implementation of ML/AI SW stack, kernels, and runtime software to improve performance and power efficiency.


• Collaborating with our AI Processor Hardware team to implement high-quality solutions for new ML operators/layers that optimally utilize new capabilities in next‑gen AI processors.


• Development of debugging/profiling tools and user‑friendly SDKs for customers to foster rapid deployment of their new use cases.

Preferred Skills And Experience

• 5+ years of experience with Machine Learning frameworks and Deep Learning (Pytorch).


• 5+ years of experience with one or more programming language suitable for machine learning (e.g., Python, C, C++)


• Strong software design, development, and debugging skills.


• Knowledge of Android programming is plus.


• Optimization of algebraic operations in algorithms for HW cores is a plus.


• Knowledge in neural network model training is a big plus.


• Knowledge in neural network model quantization is a big plus.


• Experience with Qualcomm QNN SDK is a big plus.

EEO Employer

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‑[e-mail] 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).

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

$194,400.00 - $291,600.00

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.