On-Device Machine Learning Optimization Engineer

About the Company

Our client is a leading design house specializing in the development of connected consumer electronics and IoT devices. With a strong presence across the U.S. and a global footprint, they are renowned for tackling some of the market's most complex projects. Their culture emphasizes collaboration, knowledge sharing, and work-life balance, inspired by Scandinavian values. This is a fantastic opportunity to join a team that fosters innovation while supporting individual growth and well-being.

The Opportunity

Our client is seeking a highly skilled On-Device Machine Learning Power and Performance Optimization Engineer to join their Wearable Systems team in San Diego. This role involves optimizing power and performance for advanced AR / VR and mixed-reality devices, with a focus on embedded systems, ML accelerators, and model optimization.

Responsibilities

Power and Performance Analysis :

Collect and analyze power and performance data for ML benchmarks such as MLPerf-Tiny.

• Execute benchmarks across different configurations, including accelerators and runtime environments.
• Provide detailed characterizations of ML accelerators.

Workload Optimization :

Define workload partitioning strategies based on power and performance metrics.

AI Use Case Enhancement :

Analyze power and performance traces for AI-driven use cases.

Collaborative Development :

Work closely with system architects, hardware engineers, and software teams to deliver optimized solutions.

Key Qualifications

Minimum Requirements :

Preferred Qualifications :

What Makes This Opportunity Unique

Our client is offering the chance to work on pioneering technologies for wearable and IoT devices. They value individuals who are proactive, collaborative, and eager to learn new tools and methods. This role combines innovation with the support of a highly skilled and dynamic team.

Salary : $150,000 - $180,000