LLM Engineer

Responsibilities

• Leverage advanced Machine Learning knowledge to extend training or runtime frameworks and model efficiency software tools.
• Model, architect, and develop advanced machine learning hardware co-designed with software for inference or training solutions.
• Develop optimized software to enable AI models deployed on hardware, including machine learning kernels, compiler tools, and model efficiency tools.
• Collaborate with hardware teams for joint design and development to allow for specific hardware feature utilization.
• Develop, adapt, or prototype novel machine learning solutions aligned with product roadmaps.
• Oversee and conduct experiments to train and evaluate machine learning models and software.

Requirements

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field with 4+ years of relevant work experience.
• Master's degree in a related field with 3+ years of relevant work experience.
• PhD in a related field with 2+ years of relevant work experience.
• Experience with Machine Learning frameworks (e.g., TensorFlow, PyTorch, Keras).
• Proficiency in programming languages suitable for machine learning such as Python, R, C, or C++.
• Knowledge of statistics and probability (e.g., conditional probability, Bayes rule).
• Experience in embedded system development.

Preferred Qualifications

• 5+ years of experience in embedded system development and optimization applied to ML domains like NLP or multi-media.
• 2+ years of experience with low-level interactions between operating systems (Linux, Android, QNX) and hardware.
• Experience working in a large matrixed organization.
• Previous experience in a technical leadership role.
• Experience interacting with senior leadership.

About the Company

Qualcomm is a leading technology innovator that pushes the boundaries of what's possible to enable next-generation experiences and drive digital transformation. We collaborate across cross-functional teams to enhance the world of mobile, edge, auto, and IoT products through advanced machine learning hardware and software.