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 Machine Learning Engineer, you will create and implement machine learning techniques, frameworks, and tools that enable the efficient discovery and utilization of state-of-the-art machine learning solutions over a broad set of technology verticals or designs. Qualcomm Engineers collaborate with cross-functional teams to enhance the world of mobile, edge, auto, and IOT products through machine learning hardware and software.
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).
• 4+ years in a technical leadership role with or without direct reports (only applies to positions with direct reports).
• 4+ years experience working in a large matrixed organization.
• 3+ years of work experience in a role requiring interaction with senior leadership (e.g., Sr. Director and above).
• Developed 1+ novel Machine Learning architecture(s).
Principal Duties and Responsibilities:
• Leverages expert Machine Learning knowledge to extend training or runtime frameworks or model efficiency software tools with new features and optimizations.
• Acts a technical expert for modeling, architecture, and developing highly advanced machine learning hardware (co-designed with machine learning software) for inference or training solutions.
• Develops highly 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.
• Oversees the development and application of machine learning techniques into products and/or AI solutions to enable customers to do the same.
• Acts as a technical lead for teams developing, adapting, and prototyping machine learning solutions; reviews and helps write proposals or roadmaps for sub-systems of complex products and features.
• Provides technical expertise for experiments that train and evaluate machine learning solutions and communicates progress to key stakeholders.
Level of Responsibility:
• Provides supervision to direct reports.
• Decision-making is critical in nature and highly impacts program, product, or project success.
• Requires verbal and written communication skills to convey highly complex and/or detailed information. May require strong negotiation and influence with large groups or high-level constituents.
• Develops and administers budgets, schedules, and performance standards for functional area within the prescribed budgetary objectives of the department.
• Has influence over the formulation and achievement of long-term business plans and objectives.
• Tasks often require multiple steps which can be performed in various orders; extensive planning, problem-solving, and prioritization must occur to complete the tasks effectively.
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