Qualcomm Deep Learning SW Engineer– Qualcomm Research in Seoul, South Korea
Qualcomm Korea YH
Engineering Group, Engineering Group > Machine Learning Engineering
Qualcomm is a company of inventors that unlocked 5G ushering in an age of rapid acceleration in connectivity and new possibilities that will transform industries, create jobs, and enrich lives. But this is just the beginning. It takes inventive minds with diverse skills, backgrounds, and cultures to transform 5Gs potential into world-changing technologies and products. This is the Invention Age - and this is where you come in.
Creates advanced machine learning techniques that enable a broad set of technology verticals or designs and extends training or runtime frameworks or model efficiency software tools with new features and optimizations. Models, architects, and develops advanced machine learning hardware (co-designed with machine learning software) for inference or training solutions. These enable the discovery and improvement of state-of-the-art machine learning solutions that have general applicability at the functional platform level towards audio, camera, graphics, video, sensors, wireless, and other functionality over various operating systems running on ARM processors and other embedded hardware like DSP/NSP processors, GPU processors that are embedded into mobile, edge, auto, and IoT products, or on data center based systems such as GPUs or dedicated AI hardware. Develops optimized software to enable AI models efficiently deployed on hardware, such as machine learning kernels, compiler tools, or model efficiency tools, to make sure of specific hardware features, and/or working closely with hardware teams for joint design and development. Works with and/or optimizes machine learning software frameworks like TensorFlow or PyTorch to efficiently run machine learning algorithms on hardware.
Principal Duties and Responsibilities:
• Participates in and shares own perspective within domain of machine learning subject matter expertise in design or project reviews, and project meetings.
• Takes responsibility for small projects or owns part of a larger project and completes tasks in a timely manner according to project requirements; seeks assistance when needed to solve problems and helps other team members; collaborates with cross-functional peers on tasks when needed.
• Completes complex tasks and solves issues related to the engineering and management of machine learning data with minimal guidance from more experienced engineers.
• 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.
• Creates and executes complex methods to optimize new or existing machine learning algorithms, models, kernels, and execution frameworks; suggests possible solutions to issues and documents lessons learned.
• Assists with the integration of machine learning algorithms into a platform or product for production; helps resolve issues during implementation.
• Seeks essential knowledge of machine learning industry trends, competitors' products, and advances within area of expertise from publicly available information and research; shares this information with others on the team.
Level of Responsibility:
• Working under some supervision.
• Providing some supervision/guidance to others.
• Taking responsibility for own work and making decisions with limited impact; impact of decisions is readily apparent; errors made typically only impact timeline (i.e., require additional time to correct).
• Using verbal and written communication skills to convey information that may be somewhat complex to others who may have limited knowledge of the subject in question. May require basic negotiation and influence, cooperation, tact, and diplomacy, etc.
• Having a moderate amount of influence over key organizational decisions (e.g., is consulted by senior leadership to provide input on key decisions).
• Completing most tasks with multiple steps which can be performed in various orders; some planning and prioritization must occur to complete the tasks effectively; mistakes may result in some rework.
• Exercising creativity to draft original documents, imagery, or work products within established guidelines.
• Using deductive and inductive problem solving; multiple approaches may be taken/necessary to solve the problem; often information is missing or conflicting; advanced data analysis and interpretation skills are required.
• May be solicited during strategic planning period.
The responsibilities of this role do not include:
• Financial accountability (e.g., does not involve budgeting responsibility).
• Master's degree in Computer Science, Engineering, Information Systems, or related fields.
• 2+ years of experience with Machine Learning frameworks (e.g., Tensor Flow, Caffe, Caffe 2, PyTorch, Keras).
• 2+ years of experience in embedded system development and optimization with application to a specific problem domain in ML (e.g., NLP, multi-media).
• 2+ years of experience with one or more programming languages suitable for machine learning (e.g., Python, R, C, C++)
• 2+ years of experience using statistics and probability (e.g., conditional probability, Bayes rule).
• 1+ years of experience with low level interactions between operating systems (e.g., Linux, Android, QNX) and Hardware.
• 2+ years experience working in a large matrixed organization.
• 1+ years of work experience in a role requiring interaction with senior leadership (e.g., Director and above).
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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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