AI Hardware Systems Manager, Annapurna Labs, Trainium Machine Learning Fleet Operations

Amazon.com Inc

Austin, TX

JOB DETAILS
SKILLS
Amazon Web Services (AWS), Artificial Intelligence (AI), Automation, Career Counseling, Cloud Computing, Coaching, Computer Engineering, Corrective Action, Cross-Functional, Customer Experience, Customer Support/Service, Data Visualization, Debugging Skills, Diving, Establish Priorities, Hardware Debugging, Hardware Design, Incident Response, Laboratory, Leadership, Machine Learning, Machine Tool, Machining Operations, Mentoring, Metrics, Multiplatform/Cross-Platform, Operational Audit, Scalable System Development, Server Hardware, Service Level Agreement (SLA), Software Design, Software Development, Software Engineering, Systems Administration/Management, Team Lead/Manager, Technical Leadership, Technical Strategy, Vehicle Fleets
LOCATION
Austin, TX
POSTED
9 days ago

Annapurna Labs designs silicon and software that accelerates innovation. Customers choose us to create cloud solutions that solve challenges that were unimaginable a short time ago, even yesterday. Our custom chips, accelerators, and software stacks enable us to take on technical challenges that have never been seen before, and deliver results that help our customers change the world.

In Annapurna Labs we are at the forefront of hardware/software co-design not just in Amazon Web Services (AWS) but across the industry. The Machine Learning Acceleration Fleet Operations Team is looking for a technical leader to manage a team of 5-10 engineers and own operations across multiple ML server platforms spanning tens of thousands of hosts globally.

We are seeking a manager who combines strong technical depth in hardware systems and software development with proven people leadership. You will build and grow a high-performing team, set technical direction for fleet-scale automation and tooling, and drive operational excellence across some of the most advanced server hardware in existence. You will define your team"s 6-12 month roadmap, influence org-level priorities, and represent fleet operations in VP-level reviews. You are equally comfortable debugging a complex hardware failure as you are coaching an engineer through a career development conversation.

Our team has end to end ownership of some of the most advanced server hardware in the world. We drive technical debug efforts and write truly massive scale autonomous software to monitor, optimize, and remediate machine learning hardware. Come define how we operate the future of ML infrastructure.

Key job responsibilities

  • Build, hire, mentor, and grow a team of platform development engineers responsible for ML fleet operations across multiple accelerator platforms
  • Define team roadmap and technical strategy for fleet health, automation, and data infrastructure - balancing near-term operational demands against long-term engineering investments
  • Drive operational excellence by establishing metrics, SLAs, and processes that maximize platform sellability and customer experience
  • Partner with hardware engineering, software engineering, and product teams to prioritize debug efforts and translate fleet learnings into permanent design fixes
  • Own escalation paths for critical fleet incidents and lead cross-functional war rooms to resolution
  • Influence org-level priorities by surfacing fleet-wide patterns and advocating for systemic improvements across the ML hardware portfolio
  • Raise the bar on team software practices - ensuring automation is maintainable, tested, documented, and reusable at scale
  • Represent fleet operations in executive reviews, providing data-driven narratives on platform health and roadmap

A day in the life

As a Manager on the MLA Fleet Operations team, you set the direction for how your team keeps the world"s most advanced ML accelerators healthy at scale.

You start each day with your people - holding 1:1s, coaching engineers through ambiguous technical problems, removing blockers, and ensuring the team is focused on the highest-impact work. From there, you review fleet health with the team, understanding which issues are trending, which investigations need unblocking, and where to allocate engineering effort for maximum customer impact. You partner with hardware design teams to advocate for fleet-informed design changes and with service teams to align on deployment schedules. You balance long-term automation investments against near-term operational demands, and you represent your team"s work to senior leadership with clear data and crisp narratives. When critical incidents arise, you lead the response - marshaling the right people, driving root cause, and ensuring corrective actions land.

About the team

The MLA Fleet Operations team was formed to maintain an exceptionally high quality bar for our fleet of advanced machine learning accelerators and server products. We perfect the customer experience by developing scalable software for rapid incident response times and data visualization as well as diving deep into hardware 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