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

Amazon is hiring an AI Hardware Systems Manager, Annapurna Labs, Trainium Machine Learning Fleet Operations in Austin, United States. It pays $175k-$237k a year and Level rates it ; you can apply on Amazon.

Level's read on this job

Level rates this role Builds AI ●●●●: the job is building AI systems.
The posting mentions AWS, hardware systems and fleet operations among its tools and skills.
Level classes it as a lead role.
Amazon has 20,000+ other open roles on Level.

AI in this role

Manage machine learning fleet operations and infrastructure for Annapurna Labs at AWS.

AWS

hardware-systemsfleet-operationsautomationmachine-learning-infrastructure

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.

Basic qualifications

- Bachelor's degree in computer science, electrical engineering, or related field
- 2+ years of engineering team management experience
- Knowledge of and proficiency in the use of Python scripting language
- Experience with general troubleshooting/debugging of hardware
- Experience designing, building, operating, and managing large-scale distributed systems or web services
- 7+ years of experience in systems engineering, platform engineering, SRE, or hardware operations

Preferred qualifications

- Experience in automating, deploying, and supporting large-scale infrastructure
- Experience in server technologies such as, thermal, mechanical, power, and signal integrity
- Experience working cross-functionally across several teams both technical and non-technical
- Experience with GPU, ML accelerator, or high-performance computing hardware
- Experience managing teams through ambiguity on new or unreleased products

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, TX, Austin - 175,100.00 - 236,900.00 USD annually

How we rate this

AI Hardware Systems Manager, Annapurna Labs, Trainium Machine Learning Fleet Operations at Amazon rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

AI Hardware Systems Manager, Annapurna Labs, Trainium Machine Learning Fleet Operations is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $175k-$237k a year.
The role is based in US, TX, Austin.
The job was posted on June 15, 2026.
Seniority: lead.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Hardware SystemsFleet OperationsAutomationMachine Learning InfrastructureAWS

Questions you could be asked

Tell me about a project where hardware systems was part of your work. What did you do?
Tell me about a project where fleet operations was part of your work. What did you do?
Tell me about a project where automation was part of your work. What did you do?
Tell me about a project where machine learning infrastructure was part of your work. What did you do?
Walk me through how you've used AWS in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Hardware Systems, Fleet Operations, Automation, Machine Learning Infrastructure, and AWS. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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