Company:Qualcomm Technologies, Inc.

Job Area:Engineering Group, Engineering Group > Machine Learning Researcher

General Summary:

Qualcomm AI Research is a high-caliber global team of researchers and engineers focused on AI technology innovation, from fundamental research to on-device full-stack innovation. We build advanced machine learning technology to provide best-in-class solutions in performance while running with the most efficient use of power, memory, and computation. Our contributions have been instrumental in advancing generative AI prototypes and system solutions on the Snapdragon AI platform, with state-of-the-art methods such as low-bit vector quantization, distillation and efficient model architecture design for LVM, LMM, and LLMs, and system algorithms such as speculative decoding. You will be part of a multi-disciplinary research and engineering team spanning software, hardware, and systems. See your design in action on industry-leading chips embedded in the next generation of smartphones, cloud, autonomous vehicles, robotics, and IOT devices.  

This position is for a Principal or Sr. Director level Generative AI System Engineer who can drive the development of new technologies and their deployment onto robust proof-of-concept demonstrations or reference designs for commercial systems. The candidate is expected to provide: 
 

Robust design and operation of generative AI systems, through definition of system goals, analysis of options, thorough performance evaluation and down-selection, and final verification that solution meets goals 

Deliver full-stack system reference designs that can lead to proof-of-concept demonstrations or later commercial releases and related IP development  

Contribute to core machine learning research and system designs, e.g., related to LVM, LLM, and LMMs, multi-modal real-time streaming systems, agentic systems, test-time compute scaling. 

Contribute to new models or new training methods in various technology areas, e.g. deep generative models, Bayesian deep learning, few-shot learning, reinforcement learning, unsupervised learning 

Drive systems innovations to improve efficiency for AI on edge and mobile devices as well as in hybrid AI systems involving the edge and cloud, 

Enable new uses cases and achieve state-of-the-art performance in on-device applications, and/or impact other core Qualcomm businesses e.g., wireless, audio/speech camera image, video and 3D, ADAS, and XR. 

 

Minimum Qualifications:

• Master's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field and 10+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
OR
PhD in Computer Engineering, Computer Science, Electrical Engineering, or related field and 8+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

• 6+ months of experience developing and/or optimizing machine learning models, systems, platforms, or methods.

Preferred Qualifications:

PhD in Computer Science, Engineering, or related field 

Extensive experience in deep neural networks (e.g., CNN, RNN, Graph-NN, Attention, Vision-and Language-based Transformers), generative AI (e.g., latent diffusion, auto-regressive transformers, state-space models), or deep reinforcement learning.  

Extensive experience with full-stack systems involving SW / FW / HW and embedded systems; knowledge of AI stack, including Qualcomm AI Runtime (QAIRT), TensorFlow Lite, ONNX Runtime, ExecuTorch, and AI accelerators and cores such as the Hexagon NPU, Adreno GPU, 8 Elite / X Elite CPU.  

Proficiency in designing, implementing, and training algorithms in high-level languages/frameworks such as PyTorch, TensorFlow, JAX.   

Track record of system engineering excellence and experience with high-quality publications and thorough analysis of complex systems with ablations. 

Expertise in at least one of the following fields: Generative AI; Deep Generative Models (e.g., VAE, Normalizing-Flow, ARM); Machine learning theory / optimization methods; Model compression / quantization / optimization for embedded devices / kernel optimization; Unsupervised and Self-supervised learning; Reinforcement Learning; Deep learning for time-series; Computer vision; Audio and speech / NLP 

Principal Duties and Responsibilities:

•    Leverages expert Machine Learning knowledge to influence and oversee the fundamental research to create new models or training methods in various technology areas (e.g., deep generative models, Bayesian deep learning, equivariant CNNs, Bayesian optimizations, reinforcement learning, unsupervised learning, and graph NNs).

•    Directs and oversees systems innovations for model efficiency advancement on device as well as in the cloud, including auto-ML methods for the creation and optimization of efficient models (e.g., model compression, quantization, architecture search, and kernel/graph compiler/scheduling).

•    Determines guidelines for performing platform research to enable new machine learning compute paradigm (e.g., compute in memory, on-device learning/training, edge-cloud distributed/federated learning, and quantum machine learning).

•    Develops and publishes research findings in the form of presentations and conference papers.

•    Partners with senior stakeholders across the business to create the strategy for research programs across multiple technologies or products related to machine learning and executes on research proposals of various levels of complexity.

•    Drives innovation in ideas and solutions based on current and future industry trends.

•    Sets strategies to develop, test, optimize, and document new or updated machine learning algorithms, models, and methods.

Level of Responsibility:  
•    Provides supervision to other supervisors/managers who are direct reports.
•    Decision-making is critical in nature and highly impacts program, product, or project success.
•    Requires verbal and written communication skills to convey highly complex and/or detailed information. May require strong negotiation and influence with large groups or high-level constituents.
•    Develops and administers budgets, schedules, and performance standards for functional area within the prescribed budgetary objectives of the department.
•    Has influence over the formulation and achievement of long-term business plans and objectives.
•    Tasks often require multiple steps which can be performed in various orders; extensive planning, problem-solving, and prioritization must occur to complete the tasks effectively.

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).

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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:

$263,700.00 - $395,500.00

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.