Silicon Power Engineer

Meta•Redmond, WA

22h

About The Position

Reality Labs focuses on delivering Meta's roadmap through creating advanced AI enabled wearables. The compute performance and power efficiency requirements of wearables require custom silicon. Reality Labs Silicon team is driving the state-of-the-art forward with breakthrough work in AI, augmented reality, computer vision, machine learning, graphics, displays, and sensors. Our chips will enable wearable devices where our real and virtual world will mix and match throughout the day. We are growing our team and are seeking engineers who will work with a group of individuals using your skills to implement and contribute to the development and optimization of accelerators for emerging technologies and applications.

Requirements

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
6+ years of experience as an engineer for production silicon
Experience employing scientific methods to debug, diagnose and drive the resolution of cross-disciplinary system issues
Knowledge of Silicon trade-offs in design and back end implementation
Experience with Power Technology - Power Exchange, Power Artist or other power analysis/simulation tools
Experience with Python, TCL, Perl programming

Nice To Haves

Master/PhD degree in Electrical Engineering, Computer Science and/or equivalent work experience
6+ years of experience as Power engineer for production silicon
Experience with Silicon power measurement, correlation and modeling
Experience with CPU/GPU/Custom ASIC early power projections and modeling with feedback from silicon
Experience with creating power model and estimating power for different IPs, working with IP owners in defining IP level targets and knowledge of use case power analysis
Experience working with EDA tools like Fusion Compiler, ICC2/Innovus
Experience in hardware microarchitecture or RTL design

Responsibilities

Detailed modeling, analysis and optimization of silicon use case power for Machine Learning Hardware accelerator, and create detailed cost/benefit analysis
Collaborate with ML architects and designers to understand the ML workloads and develop recipes to optimize the PPA of ML compute datapath design blocks
Work across disciplines, brainstorm big ideas, work in new technology areas, juggle/coordinate multiple initiatives, drive a concept into a prototype and ultimately guide the transition into a high-volume consumer product
Travel both domestically and internationally