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Job Area:
Engineering Group, Engineering Group > Machine Learning Researcher
You have a background in one or more of the following: optimization, model quantization, model compression, dynamic sparsity and MoEs, or classical search algorithms. You have experience with LLMs, Vision-Language Models, Multi-modal Models, or related AI models, demonstrated through publications in top-tier conferences.
Minimum qualifications:
PhD or Master’s degree in Machine Learning, Computer Vision, Physics, Mathematics, Electrical engineering or similar field, or equivalent practical experience
Experience in machine learning, deep learning, and/or reinforcement learning
Ability to formulate research problems and design, experiment and implement solutions
Programming experience in Python and hands-on experience with deep learning toolkits such as PyTorch, TensorFlow, Jax
Preferred qualifications:
Track record of publishing at major conferences in machine learning (NeurIPS, ICML, ICLR, CVPR, etc.)
Hands-on experience with foundation models (LLMs, LVMs) is a strong plus
Experience in writing clean and maintainable code for research-internal use (no product development)
Experience working in an academic or industry research lab
Minimum Qualifications:
• Master's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
PhD in Computer Engineering, Computer Science, Electrical Engineering, or related field.
• 6+ months of academic and/or work experience developing and/or optimizing machine learning models, systems, platforms, or methods.
*References to a particular number of years experience are for indicative purposes only. Applications from candidates with equivalent experience will be considered, provided that the candidate can demonstrate an ability to fulfill the principal duties of the role and possesses the required competencies.
Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.
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