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

Amazon; Austin (TX); On-site; USD 175,100 - 236,900; Full time

Benefits offered by this job

Health insurance

401(k) matching

Sign-on payments

Job summary

Amazon in Austin, Texas is seeking an AI Hardware Systems Manager to lead the ML fleet operations team. You will mentor engineers and drive operational excellence by establishing metrics to maximize platform health and customer experience.

The ideal candidate holds a Bachelor's in Computer Science or Electrical Engineering and has over 7 years of experience in systems engineering or hardware operations. Benefits include a comprehensive package with health insurance and stock units.

Qualifications

• 2+ years of engineering team management experience.
• 7+ years of experience in systems engineering or hardware operations.
• Experience with general troubleshooting/debugging of hardware.

Responsibilities

• Build, mentor, and grow a team of platform development engineers.
• Define team roadmap and technical strategy for fleet health.
• Drive operational excellence by establishing metrics and processes.

Skills

Python scripting language

Engineering team management

Troubleshooting/debugging hardware

Designing large-scale distributed systems

Machine learning hardware experience

Education

Bachelor's degree in Computer Science or Electrical Engineering

Job description

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

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.

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.

Benefits

Salary Range: 175,100.00-236,900.00 USD annually. 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 optional 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.

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