Qualcomm Technologies, Inc.
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.
This individual 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. This individual may also model, architect, and develop 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 has general applicability at 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. Other responsibilities include developing 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. In this regard, the individual may need to work with and/or optimize machine learning software frameworks like Scikit-Learn or TensorFlow or to efficiently run machine learning algorithms on hardware.
The responsibilities of this role include:
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).
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.
REQUIRED COMPETENCIES: (All competencies below are required upon entry)
Analytical Skills - The ability to collect information and identify fundamental patterns/trends in data. This includes the ability to gather, integrate, and interpret information from several sources.
Building Trusting Relationships - The ability to build trusting, collaborative relationships and rapport with different types of people and businesses. This includes delivering on commitments and maintaining confidential information, as well as being approachable, and relating well to people regardless of personality or background.
Communication - The ability to convey information clearly and accurately, as well as to choose the most effective method of delivery (e.g., email, phone, face-to-face) for technical and non-technical information.
Creating the New and Different - The ability to be creative. This includes the ability to produce breakthrough ideas, being a visionary, managing innovation, having broad interests and knowledge, and gaining support in order to translate new ideas into solutions.
Decision-Making - The ability to make quick, accurate decisions. This includes the ability to weigh alternatives and take into account the impact of the decisions on people, equipment, or other resources.
Getting Work Done - The ability to be organized, resourceful, and planful. This includes the ability to leverage available resources to get things done and lay out tasks in sufficient detail. This also includes the ability to work on multiple tasks at once without losing track and foresee and plan around obstacles.
Technical Knowledge - The ability to understand and apply key machine learning concepts, frameworks, techniques, and tools to create innovative, accurate, robust, and high-quality solutions.
Software Development – The ability to collaborate in the development software and data pipelines required to Machine Learning models.
Frequently transports between offices, buildings and campuses up to ½ mile.
Frequently transports and install equipment up to 5 lbs.
Performs required tasks at various heights (e.g. standing or sitting).
Monitors and utilizes computers and test equipment for more than 6 hours a day.
Continuous communication which includes the comprehension of information with colleagues, customers and vendors both in person and remotely.
Bachelors - Computer Science, Bachelors - Engineering, Bachelors - Information Systems
2+ years Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.
Masters - Computer Science, Masters - Engineering, Masters - Information Systems
2+ years experience with one or more programming language suitable for machine learning (e.g., Python, R, C, C++). ,1+ years of experience with low level interactions between operating systems (e.g., Linux, Android, QNX) and Hardware ,2+ years experience using statistics and probability (e.g., conditional probability, Bayes rule) ,2+ years experience in embedded system development and optimization with application to a specific problem domain in ML (e.g., NLP, multi-media). ,2+ years experience with Machine Learning frameworks (e.g.,Tensor Flow, Caffe, Caffe 2, Pytorch, Keras) ,1+ years of work experience in a role requiring interaction with senior leadership (e.g., Director level and above). ,2+ years of experience working in a large matrixed organization.
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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.
If you would like more information about this role, please contact Qualcomm Careers .