Staff Machine Learning Engineer: Edge AI & Hardware

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

Benefits offered by this job

Competitive benefits

Job summary

Qualcomm Innovation Center, Inc. seeks a Machine Learning Engineer to create and implement ML techniques, frameworks, and tools enabling state-of-the-art solutions across mobile, edge, auto, and IoT domains.

Collaborate with cross-functional teams to advance ML hardware and software for a smarter, connected future. Responsibilities include developing optimized ML software, prototyping novel ML solutions, and leading experiments to evaluate models.

Qualifications

• Bachelor's degree with 4+ years of Hardware/Software/Systems experience.
• Master's degree with 3+ years of related experience.
• PhD with 2+ years of related experience.

Responsibilities

• Leverages advanced ML knowledge to extend training or runtime frameworks and model efficiency tools.
• Develops ML hardware (co-designed with ML software) for inference or training solutions.
• Develops optimized software to enable AI models on hardware (kernels, compilers, efficiency tools).
• Applies ML techniques to products and AI solutions for customers.
• Prototypes novel ML solutions aligned with proposals/roadmaps for complex products.
• Oversees experiments to train and evaluate ML models.

Skills

Machine Learning

Team collaboration

Verbal and written communication

Education

Bachelor's degree in CS/Engineering

Master's degree in CS/Engineering

PhD in CS/Engineering

Tools

TensorFlow

Caffe

Caffe2

PyTorch

Keras

Python

C

C++

Linux

Android

QNX

Job description

Qualcomm Innovation Center, Inc. seeks a Machine Learning Engineer to create and implement ML techniques, frameworks, and tools enabling state-of-the-art solutions across mobile, edge, auto, and IoT domains.

Collaborate with cross-functional teams to advance ML hardware and software for a smarter, connected future. Responsibilities include developing optimized ML software, prototyping novel ML solutions, and leading experiments to evaluate models.