Auto AI Systems: Team Lead Full-time

Company:
Qualcomm Technologies, Inc.

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

General Summary:

We are seeking a highly qualified AI Systems Team Lead who will be responsible for overseeing a team of machine learning engineers in the design and implementation of state-of-the-art low-level perception (LLP) and end-to-end autonomous driving (AD) models, with a focus on achieving accuracy-latency Pareto optimality.

The team will be tasked with designing state-of-the-art Low-Level Perception systems as well as end-to-end AD design and deployment on the Qualcomm Ride platform for L2/L3 ADAS/Autonomous driving. Additionally, the team will be responsible for enhancing the speed, accuracy, power consumption, and latency of deep networks operating on Snapdragon Ride AI accelerators.

The ideal candidate must be well-versed in recent advancements in Vision Transformers (Cross Attention, Self-Attention), lifting 2D features to BEV space, and their applications to multi-modal fusion. The role requires facilitating collaboration with various Qualcomm horizontal AI teams.

Furthermore, the candidate will be responsible for engaging with advanced R&D teams of leading Automotive OEMs as well as Qualcomm’s internal stack teams.

A strong knowledge of machine learning algorithms, particularly those related to automotive use-cases (autonomous driving, vision, and lidar processing ML algorithms), is essential. Research experience in the development of efficient networks, various Neural Architecture Search (NAS) techniques, network quantization, and pruning is highly desirable.

The candidate will also be responsible for building a team of world-class AI/deep learning engineers.

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:

• PhD in related field with 5+ years of relevant experience, master’s with 10+ years, or Bachelor of engineering with 12+ years of relevant experience.
• Previous experience in leading ML engineers.
• Strong interest towards team leadership, cross functional collaboration and mentoring/guiding new team members.
• Strong understanding of Machine Learning fundamentals with multiple external publications/patents.
• Hands-on experience with deep learning network design and implementation.
• Good at software development with excellent analytical, development, and problem-solving skills.
• Experience in deep learning kernel/compiler optimization.
• Strong communication and interpersonal skills are required.

Principal Duties and Responsibilities:
• Leverages advanced Machine Learning knowledge to extend training or runtime frameworks or model efficiency software tools with new features and optimizations.
• Models, architects, and develops highly advanced machine learning hardware (co-designed with machine learning software) for inference or training solutions.
• Develops critical optimized software to enable AI models deployed on hardware (e.g., machine learning kernels, compiler tools, or model efficiency tools, etc.) to allow specific hardware features; collaborates with hardware teams for joint design and development.
• Leads the development and application of machine learning techniques into products and/or AI solutions to enable customers to do the same.
• Develops, adapts, or prototypes novel machine learning solutions aligned with and motivated by proposals or roadmaps for complex products and system-level features.
• Oversees and provides technical expertise to others conducting experiments to train and evaluate machine learning solutions.

Level of Responsibility:
• Works independently with minimal supervision.
• Provides supervision/guidance to other team members.
• Decision-making is significant in nature and affects work beyond immediate work group.
• Requires verbal and written communication skills to convey complex information. May require negotiation, influence, tact, etc.
• Has a moderate amount of influence over key organizational decisions (e.g., is consulted by senior leadership to make key decisions).
• Tasks do not have defined steps; 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.

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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.