AI Hardware Systems Manager, Annapurna Labs, Trainium Machine Learning Fleet Operations
Company websiteamazon.com (Amazon, opens in new tab)
Base salary $175,100 to $236,900
Employer-published annual base salary, USD. Advertised base range in Austin, TX
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationAustin, TX
- WorkplaceWorkplace not stated
- Status at last checkSource accepting applications when checked
- Last checked (3 h ago) · observed since
About this job
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
Source: Amazon · View original posting (opens in new tab)
Pay in context
This role's base floor ($175,100) is above 85% of the 112 Data & ML roles in Texas listed on this site. Their median floor is $143,670; the middle half runs from $128,868 to $159,200.
Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 8, 2026.
This listingAI Hardware Systems Manager, Annapurna Labs, Trainium Machine Learning Fleet Operations$175,100 to $236,900
Data Scientist II - AMZ10564077$175,040 to $212,800
Manager III, SecEng, AppSec AI$175,100 to $236,900
Manager, Hardware Development - GPU/Accelerator, Annapurna ML Trainium$175,100 to $236,900
Security Engineering Manager, Leo Security$175,100 to $236,900
Security Engineering Manager, Stores AppSec$175,100 to $236,900
Security Engineering Manager, Stores Org Mobile Security$175,100 to $236,900
Chart as a table
| Role | Published base |
|---|---|
| AI Hardware Systems Manager, Annapurna Labs, Trainium Machine Learning Fleet Operations (this listing) | $175,100 - $236,900 |
| Data Scientist II - AMZ10564077 | $175,040 - $212,800 |
| Manager III, SecEng, AppSec AI | $175,100 - $236,900 |
| Manager, Hardware Development - GPU/Accelerator, Annapurna ML Trainium | $175,100 - $236,900 |
| Security Engineering Manager, Leo Security | $175,100 - $236,900 |
| Security Engineering Manager, Stores AppSec | $175,100 - $236,900 |
| Security Engineering Manager, Stores Org Mobile Security | $175,100 - $236,900 |
Observed changes
- First observed on the employer's board
- Began meeting the published-salary criteria
- Observed since
- Employer-stated posting date
- 2026-06-15
Where this pay comes from
Location as the employer wrote it: US, TX, Austin
USA, TX, Austin - 175,100.00 - 236,900.00 USD annually
- Method
- Employer text, read with fixed rules and re-verified
- Checked
- Rule set
- us-base-v2
The pay passage appears in the employer's own job text. Fixed, deterministic rules located it, and the passage below was checked against the stored copy of the posting.
What we verified
- The pay figures come from the employer's own listing, quoted exactly above.
- The pay is an annual base salary in US dollars with a minimum of at least $100,000.
- The role was publicly listed on the employer's job board when last checked.
We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.