Deep Learning Research Engineer

Overview

Company:Qualcomm Technologies, Inc.

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

Job Overview:

Qualcomm is a company of inventors that unlocked 5G ushering in an age of rapid acceleration in connectivity and new possibilities that will transform industries, create jobs, and enrich lives. But this is just the beginning. It takes inventive minds with diverse skills, backgrounds, and cultures to transform 5Gs potential into world-changing technologies and products. This is the Invention Age – and this is where you come in.

GENERAL SUMMARY

Qualcomm is a company of inventors that unlocked 5G ushering in an age of wireless intelligence and new possibilities that will transform industries, create jobs, and enrich lives. With 5G and other wireless connectivity, we bring the content, control, and intelligence closer to the end-user to complement the cloud. Qualcomm AI Research is looking for world-class researchers in machine learning and deep learning. Come join a high-caliber team of engineers building advanced machine learning technology, best-in-class solutions, and friendly SW optimization tools to enable state-of-the-art networks to run on devices with limited power, memory, and computation. Led by world-renowned pioneering machine learning researcher, Max Welling, members of our team enjoy the opportunity to participate in cutting edge research while simultaneously contributing technology that will be deployed worldwide in our industry-leading devices. You will be part of a multi-disciplinary team that has repeatedly won the major deep learning competitions, such as the ImageNet large scale visual recognition challenge and visual wake word challenge. Collaborate in a cross-functional environment spanning hardware, software and systems. See your design in action on industry-leading chips embedded in the next generation of smartphones, autonomous vehicles, robotics, and IOT devices. The R&D work responsibility can include the development of new fundamental methods in the following areas- Conducts fundamental machine learning research to create new models or new training methods in various technology areas, e.g. deep generative models, Bayesian deep learning, equivariant CNNs, adversarial learning, active learning, Bayesian optimizations, reinforcement learning, unsupervised learning, and graph NNs. – Drives systems innovations for model efficiency advancement on device as well as in the cloud. This includes auto-ML methods (model-based, sampling based, back-propagation based) for model compression, quantization, architecture search, and kernel/graph compiler/scheduling with or without systems-hardware co-design. – Performs advanced 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.- Creates new machine learning models for advanced uses cases and achieve state-of-the-art performance and beyond. The use cases can broadly include audio, speech, image, video, power management, wireless, graphics, and chip design. Ideal candidates will demonstrate the following:- Bachelor’s degree in Engineering, Information Systems, Computer Science, or related field. – 2+ years Systems Engineering or related work experience. – Extensive experience in deep neural networks (e.g. CNN, RNN, Attention, ) or deep reinforcement learning. – Proficiency in designing, implementing and training DL/RL algorithms in high-level languages/frameworks (e.g. PyTorch, TensorFlow, Caffe). Designing the network for an embedded device is a plus. – Track record of research excellence and high-quality publications (e.g. NeurIPS, CVPR, ICML, ICLR, ICCV, ). – Expertise in at least one of the following fields: Machine learning theory / optimization methods; Model compression / quantization / optimization for embedded devices; Neural Architecture Search / kernel optimization; Computer vision; Audio and speech / NLP; Deep Generative Models (VAE, Normalizing-Flow, ARM, etc)Other information about the role: Conducts fundamental machine learning research to create new models or new 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. Drives systems innovations for model efficiency advancement on device as well as in the cloud. This includes auto-ML methods (model-based, sampling based, back-propagation based) for the creation and optimization of efficient models (e.g., model compression, quantization, architecture search, and kernel/graph compiler/scheduling) with or without systems-hardware co-design. Performs advanced 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. Creates new innovative machine learning methodology for advanced uses cases to achieve performance beyond the state-of-the-art. Development of and publication of research findings in the form of presentations and conference papers may also be required. The responsibilities of this role include: • Working under some supervision.• Providing some supervision/guidance to others.• Making decisions that are moderate in impact; errors may have relatively minor financial impact or effect on projects, operations, or customer relationships; errors may require involvement beyond immediate work group to correct. • Using verbal and written communication skills to convey information that may be somewhat complex to others who may have limited knowledge of the subject in question. May require basic negotiation and influence, cooperation, tact, and diplomacy, etc. • Working within prescribed budget and resources.• Having a moderate amount of influence over key organizational decisions (e.g., is consulted by senior leadership to provide input on key decisions).• Completing tasks that do not have defined steps; simultaneous use of multiple mental abilities is generally required to determine the best approach; mistakes may result in significant rework.• Exercising exceptional creativity to innovate new ideas and develop innovative products/processes without established objectives or known parameters.• Using deductive and inductive problem solving; multiple approaches may be taken/necessary to solve the problem; often information is missing or incomplete; advanced data analysis/interpretation skills may be required.• Occasionally participating in strategic planning within own area affecting immediate operations.PRINCIPAL DUTIES AND RESPONSIBILITIES: • Displays deep knowledge in a specific area of machine learning; acquires advanced knowledge of current and future industry trends, competitors’ products, and advances within and outside of area of expertise from publicly available information and research; shares knowledge with others on the team and helps less experienced engineers understand and apply advanced concepts.• Drives own and team’s research efforts within a particular domain of machine learning to inform the planning, design, and development of technologies or products in alignment with strategy and product/technology roadmap.• Proactively develops innovative or patentable and alternative ideas for new solutions, designs relevant experiments, and works on implementation.• Manages project team to complete complex tasks and troubleshoot issues related to the engineering and management of machine learning data.• Develops complex new or updated machine learning algorithms, models, and methods that are aligned with research strategies; advises team members and less experienced engineers on designs.• Leads rigorous and principled testing and analysis of algorithms, models, and methods in different scenarios to ensure concepts work across environments; interprets results and implements improvements to optimize solutions.• Translates moderately complex research results into publications, workshops, or live demonstrations to engage the research community and communicate the engineering and business impact of concepts. • Establishes identity as a thought leader and innovator within machine learning area of expertise by publishing research papers, attending and/or presenting at industry or academic conferences, and leading internal or external training and education.• Writes clear and detailed technical documentation and descriptions of research findings for complex projects to guide engineers to use or implement research.

+ Frequently transports between offices, buildings and campuses up to ½ mile.

+ Frequently transports and install equipment up to 5 lbs.

+ Performs required tasks at various heights (e.g. standing or sitting).

+ Monitors and utilizes computers and test equipment for more than 6 hours a day.

+ Continuous communication which includes the comprehension of information with colleagues, customers and vendors both in person and remotely.

Minimum Qualifications

Education:

Masters – Computer Engineering, Masters – Computer Science, Masters – Electrical Engineering

Work Experiences:

5+ years Software Engineering, Hardware Engineering, Systems Engineering, or related work experience., 6 months of experience developing and/or optimizing machine learning models, systems, platforms, or methods

Certifications:

Skills:

Preferred Qualifications

Education:

Doctorate – Computer Engineering, Doctorate – Computer Science, Doctorate – Electrical Engineering

Work Experiences:

2+ years experience with machine learning research related to new models, systems innovations, platforms, or methodology ,2+ publications at a machine learning conference ,1+ years of work experience in a role requiring interaction with senior leadership (e.g., Director level and above). ,3+ years experience working in a large matrixed organization. ,1+ years in a technical leadership role with or without direct reports (only applies to positions with direct reports).

Certifications:

Skills:

AI Frameworks, Creating the New and Different, Deep Learning, Developing Prototypes, Machine Learning, Mathematical Modeling, Python

Applicants: If you are an individual with a disability and need an accommodation during the application/hiring process, please call Qualcomm’s toll-free number found here (https://qualcomm.service-now.com/hrpublic?id=hr_public_article_view&sysparm_article=KB0039028) for assistance. Qualcomm will provide reasonable accommodations, upon request, 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. Qualcomm is an equal opportunity employer and supports workforce diversity.

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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.

If you would like more information about this role, please contact Qualcomm Careers (http://www.qualcomm.com/contact/corporate) .

We are engineers, scientists and business strategists. We are from many different countries and speak many different languages. We come from diverse cultures and have unique perspectives. Together, we focus on a single goal—we invent breakthrough technologies that transform how the world connects, computes, and communicates.

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