Company:
Qualcomm Technologies, Inc.
Job Area:
Engineering Group, Engineering Group > Machine Learning Engineering
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:
• Master's degree in Computer Science, Engineering, Information Systems, or related field.
• 5+ years of experience with Machine Learning frameworks (e.g., Tensor Flow, Caffe, Caffe 2, Pytorch, Keras).
• 5+ years of experience with low level interactions between operating systems (e.g., Linux, Android, QNX) and Hardware.
• 5+ years of experience in embedded system development and optimization with application to a specific problem domain in ML (e.g., NLP, multi-media).
• 5+ years of experience with one or more programming language suitable for machine learning (e.g., Python, R, C, C++)
• 5+ years of experience using statistics and probability (e.g., conditional probability, Bayes rule).
• 3+ years experience working in a large matrixed organization.
• 2+ years of work experience in a role requiring interaction with senior leadership (e.g., Director and above).
• 1+ year in a technical leadership role with or without direct reports (only applies to positions with direct reports).
• Developed 1+ novel Machine Learning architecture(s).
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.
Pay range and Other Compensation & Benefits:
$185,900.00 - $278,900.00
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.