Embedded ML Engineer - AI Hardware & Software

Qualcomm; San Diego (CA); On-site; USD 162,000 - 243,000; Full time

Job summary

Qualcomm Technologies, Inc. is seeking a Machine Learning Engineer to create and implement ML techniques, frameworks, and tools that enable the efficient discovery and utilization of state-of-the-art ML solutions across diverse designs.

You will collaborate with cross-functional teams to advance ML for mobile, edge, automotive, and IoT products, integrating ML software with hardware to drive performance and energy efficiency.

Qualifications

• Bachelor's, Master's, or PhD in a relevant field with progressive work experience in hardware, software or systems engineering.
• 5+ years of hands-on experience with ML frameworks and embedded ML development.
• Experience with ML in NLP, multimedia, or related domains is a plus.

Responsibilities

• Leverages advanced machine learning knowledge to extend training or runtime frameworks and model efficiency tools.
• Architects and develops ML hardware for inference or training solutions.
• Develops optimized software to enable AI models deployed on hardware (kernels, compilers) and collaborates with hardware teams.
• Develops and applies ML techniques into products and AI solutions for customers.
• Prototyping novel ML solutions aligned with proposals or roadmaps for complex products.
• Oversees experiments to train and evaluate ML models and software.

Education

Bachelor's degree in Computer Science, Engineering, Information Systems, or related field

Master's degree in Computer Science, Engineering, Information Systems, or related field

PhD in Computer Science, Engineering, Information Systems, or related field

Tools

TensorFlow

Caffe

Caffe2

PyTorch

Keras

Python

R

C

C++

Job description

Qualcomm Technologies, Inc. is seeking a Machine Learning Engineer to create and implement ML techniques, frameworks, and tools that enable the efficient discovery and utilization of state-of-the-art ML solutions across diverse designs.

You will collaborate with cross-functional teams to advance ML for mobile, edge, automotive, and IoT products, integrating ML software with hardware to drive performance and energy efficiency.