Company Qualcomm India Private Limited
Job Area Engineering Group, Engineering Group > Systems Engineering
General Summary As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Systems Engineer, you will research, design, develop, simulate, and/or validate systems-level software, hardware, architecture, algorithms, and solutions that enables the development of cutting-edge technology. Qualcomm Systems Engineers collaborate across functional teams to meet and exceed system-level requirements and standards.
Minimum Qualifications
OR
Master's degree in Engineering, Information Systems, Computer Science, or related field and 5+ years of Systems Engineering or related work experience.
OR
PhD in Engineering, Information Systems, Computer Science, or related field and 4+ years of Systems Engineering or related work experience.
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), end-to-end models and Vision-Language models(VLM)/ Vision-Language-Action models(VLA) for Autonomous Driving and Robotics use cases, 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 Autonomous driving and Robotics applications.
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, their applications to multi-modal fusion and VLM/VLA Models. 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 and Robotics use cases 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.
Preferred Qualifications
Principal Duties And Responsibilities
Level Of Responsibility
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