General Summary:
We are seeking experts with a robust background in the field of deep learning (DL) to design state-of-the-art low-level perception (LLP) as well as end-to-end AD models, with a focus on achieving accuracy-latency Pareto optimality. This role involves comprehending state-of-the-art research in this field and deploying networks on the Qualcomm Ride platform for L2/L3 Advanced Driver Assistance Systems (ADAS) and autonomous driving.
The ideal candidate must be well-versed in recent advancements in Vision Transformers (Cross-attention, Self-attention), lifting 2D features to Bird's Eye View (BEV) space, and their applications to multi-modal fusion. This position offers extensive opportunities to collaborate with advanced R&D teams of leading automotive Original Equipment Manufacturers (OEMs) as well as Qualcomm's internal stack teams. The team is responsible for enhancing the speed, accuracy, power consumption, and latency of deep networks running on Snapdragon Ride AI accelerators.
A thorough understanding 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.
Strong communication and interpersonal skills are required, and the candidate must be able to work effectively with various horizontal AI teams.
Minimum Qualifications:
• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.Preferred Qualifications:
Principal Duties and Responsibilities:
• Applies Machine Learning knowledge to extend training or runtime frameworks or model efficiency software tools with new features and optimizations.
• Models, architects, and develops machine learning hardware (co-designed with machine learning software) for inference or training solutions.
• Develops 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 team members for joint design and development.
• Assists with 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 complex machine learning algorithms, models, or frameworks aligned with and motivated by product proposals or roadmaps with minimal guidance from more experienced engineers.
• Conducts complex experiments to train and evaluate machine learning models and/or software independently.
Level of Responsibility:
• Works independently with minimal supervision.
• Decision-making may affect work beyond immediate work group.
• Requires verbal and written communication skills to convey information. May require basic 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 require multiple steps which can be performed in various orders; some planning, problem-solving, and prioritization must occur to complete the tasks effectively.
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Pay range and Other Compensation & Benefits:
$140,800.00 - $211,200.00The 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.
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