Power and Performance Validation Engineer, Annapurna Labs

Amazon.com Inc

Austin, TX

JOB DETAILS
SKILLS
Algorithms, Amazon Web Services (AWS), Analog Microwave or Power, Architectural Design, Architectural Services, Artificial Intelligence (AI), Budgeting, Cloud Computing, Computer Architecture, Computer Firmware, Computer Programming, Debugging Skills, Design Verification, Hardware Design, Home Automation, Internet Technology, Low Power, Machine Learning, Network Operations Center, Oscilloscope, Power Engineering, Power Management, Product Development, Product Lifecycle, Production Support, Production Systems, RTL Design, Reporting Dashboards, Root Cause Analysis, Silicon Bringup, Startup, Stress Testing, Technical Operations, Test Plan/Schedule, Test Strategy
LOCATION
Austin, TX
POSTED
4 days ago

Annapurna Labs, an AWS organization with development centers in the U.S. and Israel, builds custom silicon and software for AWS customers. Our team combines cloud-scale innovation with world-class expertise across silicon engineering, hardware design, verification, software, and operations to tackle technical challenges that have never been seen before.

Join our Silicon Validation team to own power validation of next-generation machine learning accelerators that power AWS"s cloud computing infrastructure. You"ll work in a fast-paced, startup-like environment alongside some of the brightest minds in the industry on advanced, internet-scale technology that directly impacts how customers use Machine Learning acceleration. We are changing the landscape of cloud infrastructure by accelerating the development of custom silicon by moving beyond traditional partnerships to dominate in AI training and inference.

Your work will span power validation across the complete vertical stack - silicon power domains, DVFS flows, power delivery networks, dynamic workload power profiling, and system-level power budgeting. You"ll validate power management schemes, characterize peak power and di/dt transient behavior, and close the loop between pre-silicon power models and silicon reality. Your measurements directly determine operating envelopes, influence architectural trade-offs, and define when silicon is ready for production deployment at AWS data center scale.

Key job responsibilities

As a Power Validation Engineer on our Machine Learning Acceleration team, you"ll own power-domain validation across the entire product development lifecycle - from early design validation through emulation, silicon bring-up, post-silicon characterization, and ongoing support of production systems deployed in AWS data centers. You"ll collaborate deeply with power architecture, RTL design, design verification, firmware, and software teams to ensure our next-generation AI/ML accelerators meet power targets and efficiency goals. This role requires bridging multiple domains - from low-level power delivery and analog measurement to workload-driven power-performance trade-offs - to deliver exceptional results.

We are looking for candidates with strong programming skills, computer architecture fundamentals, understanding of how workload behavior drives dynamic power consumption, a solid understanding of power architecture, as well as experience with power measurement, PDN characterization, and power management firmware.

A day in the life

  • Developing comprehensive power validation strategies and detailed test plans covering sequencing, DVFS, peak power, di/dt, and stress testing from silicon bring-up to product release
  • Characterizing peak power consumption and transient droop under real ML training workloads across PVT corners
  • Conducting hands-on power measurements and debug in the lab using DC power analyzers, current probes, high-bandwidth oscilloscopes, and VNA/TDR
  • Validating power management algorithms, DVFS transitions, thermal throttling, and power capping mechanisms on silicon
  • Correlating silicon power measurements against pre-silicon power models and driving model-to-silicon feedback with architecture teams
  • Building automated power regression frameworks, dashboards, and anomaly detection to track power across steppings at scale
  • Collaborating across power architecture, design, firmware, and software teams to triage power anomalies and drive root cause analysis to closure
  • Supporting production systems in AWS data centers and addressing power-related field issues as they arise

About the Company

A

Amazon.com Inc

At Amazon, we don’t wait for the next big idea to present itself. We envision the shape of impossible things and then we boldly make them reality. So far, this mindset has helped us achieve some incredible things. Let’s build new systems, challenge the status quo, and design the world we want to live in. We believe the work you do here will be the best work of your life.

Wherever you are in your career exploration, Amazon likely has an opportunity for you. Our research scientists and engineers shape the future of natural language understanding with Alexa. Fulfillment center associates around the globe send customer orders from our warehouses to doorsteps. Product managers set feature requirements, strategy, and marketing messages for brand new customer experiences. And as we grow, we’ll add jobs that haven’t been invented yet.

It’s Always Day 1
At Amazon, it’s always “Day 1.” Now, what does this mean and why does it matter? It means that our approach remains the same as it was on Amazon’s very first day – to make smart, fast decisions, stay nimble, invent, and stay focused on delighting our customers. In our 2016 shareholder letter, Amazon CEO Jeff Bezos shared his thoughts on how to keep up a Day 1 company mindset. “Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight,” he wrote. “A customer-obsessed culture best creates the conditions where all of that can happen.” You can read the full letter here

Our Leadership Principles
Our Leadership Principles help us keep a Day 1 mentality. They aren’t just a pretty inspirational wall hanging. Amazonians use them, every day, whether they’re discussing ideas for new projects, deciding on the best solution for a customer’s problem, or interviewing candidates. To read through our Leadership Principles from Customer Obsession to Bias for Action, visit https://www.amazon.jobs/principles
COMPANY SIZE
10,000 employees or more
INDUSTRY
Retail
FOUNDED
1994
WEBSITE
http://Amazon.com/militaryroles