Qualcomm
Company:
Qualcomm Technologies, Inc. Job Area:
Engineering Group, Engineering Group > Machine Learning 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 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.
Minimum Qualifications: Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 4+ 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 3+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR PhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
Role responsibilities:
Conducts fundamental machine learning research to create new models or new training methods in various technology areas, e.g., large language models, deep generative models (transformers, state-space networks, diffusion networks, VAEs), reasoning models, agentic frameworks, and reinforcement learning techniques.
Drives systems innovations for model efficiency advancement on device as well as in the cloud, including model compression, model sparsity, quantization optimization methods, and unified optimization of models and their implementation on-target to balance memory, speed, and power.
Performs advanced platform research to enable new machine learning compute paradigms, e.g., compute in memory, on-device learning/training, edge-cloud distributed/federated learning, quantum machine learning, causal and language-based reasoning.
Creates new machine learning models for advanced use cases that achieve state-of-the-art performance and beyond across areas such as computer vision, audio, speech, NLP, image, video, power management, wireless, graphics, and chip design.
Design, develop, and test software for machine learning frameworks that optimize models to run efficiently on edge devices.
Research, design, develop, enhance, and implement different components of machine learning compilers for hardware accelerators.
Design, implement, and train DL/RL algorithms in high-level languages/frameworks.
Preferred Qualifications:
PhD in AI, Computer Science, Engineering, Information Systems, or related field, or MS with 4+ years of machine learning research or related work experience.
Strong background in computer science and deep learning basics.
Strong programming skills in Python and PyTorch; proficiency in designing and implementing complex training and evaluation pipelines.
Exceptional analytical, development, debugging and problem solving skills.
Experience with LLM, LVM, LMM models, and other neural network architectures.
Excellent interpersonal, written, and oral communications skills.
Experience with machine learning accelerators, optimizing algorithms for hardware acceleration cores, working with heterogeneous or parallel computing systems.
Design and develop generalized AI solutions, including retrieval and agentic systems.
Experience in LLM reasoning or inference acceleration research; on-device AI model production or exposure to mobile/edge device environments.
First author publications experience at major AI conferences, e.g., NeurIPS, ICML, and ICLR.
Additional Information: Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, Qualcomm is committed to providing an accessible process. 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. Qualcomm expects its employees to abide by all applicable policies and procedures, including security requirements regarding protection of confidential information.
Pay range and Other Compensation & Benefits:
$160,500.00 - $240,700.00. The pay scale reflects the broad, minimum to maximum, for the job code/location. Salary is one component of total compensation, with additional benefits, bonus programs, and RSU grants; discuss details with your recruiter. For more information about benefits, please refer to Qualcomm's resources.
If you would like more information about this role, please contact Qualcomm Careers.
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Qualcomm Technologies, Inc. Job Area:
Engineering Group, Engineering Group > Machine Learning 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 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.
Minimum Qualifications: Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 4+ 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 3+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR PhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
Role responsibilities:
Conducts fundamental machine learning research to create new models or new training methods in various technology areas, e.g., large language models, deep generative models (transformers, state-space networks, diffusion networks, VAEs), reasoning models, agentic frameworks, and reinforcement learning techniques.
Drives systems innovations for model efficiency advancement on device as well as in the cloud, including model compression, model sparsity, quantization optimization methods, and unified optimization of models and their implementation on-target to balance memory, speed, and power.
Performs advanced platform research to enable new machine learning compute paradigms, e.g., compute in memory, on-device learning/training, edge-cloud distributed/federated learning, quantum machine learning, causal and language-based reasoning.
Creates new machine learning models for advanced use cases that achieve state-of-the-art performance and beyond across areas such as computer vision, audio, speech, NLP, image, video, power management, wireless, graphics, and chip design.
Design, develop, and test software for machine learning frameworks that optimize models to run efficiently on edge devices.
Research, design, develop, enhance, and implement different components of machine learning compilers for hardware accelerators.
Design, implement, and train DL/RL algorithms in high-level languages/frameworks.
Preferred Qualifications:
PhD in AI, Computer Science, Engineering, Information Systems, or related field, or MS with 4+ years of machine learning research or related work experience.
Strong background in computer science and deep learning basics.
Strong programming skills in Python and PyTorch; proficiency in designing and implementing complex training and evaluation pipelines.
Exceptional analytical, development, debugging and problem solving skills.
Experience with LLM, LVM, LMM models, and other neural network architectures.
Excellent interpersonal, written, and oral communications skills.
Experience with machine learning accelerators, optimizing algorithms for hardware acceleration cores, working with heterogeneous or parallel computing systems.
Design and develop generalized AI solutions, including retrieval and agentic systems.
Experience in LLM reasoning or inference acceleration research; on-device AI model production or exposure to mobile/edge device environments.
First author publications experience at major AI conferences, e.g., NeurIPS, ICML, and ICLR.
Additional Information: Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, Qualcomm is committed to providing an accessible process. 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. Qualcomm expects its employees to abide by all applicable policies and procedures, including security requirements regarding protection of confidential information.
Pay range and Other Compensation & Benefits:
$160,500.00 - $240,700.00. The pay scale reflects the broad, minimum to maximum, for the job code/location. Salary is one component of total compensation, with additional benefits, bonus programs, and RSU grants; discuss details with your recruiter. For more information about benefits, please refer to Qualcomm's resources.
If you would like more information about this role, please contact Qualcomm Careers.
#J-18808-Ljbffr