AI Hardware Systems Engineer, 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.

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 candidates interested in

diving deep into our fleet of ML servers deployed around the world.

We are seeking an engineer who is comfortable debugging emergent problems in GPU

and server hardware, writing scripts in languages such as Python or Bash,

running large scale experiments on a fleet of complex hardware, developing data

infrastructure and analyzing trends, and developing automation software to scale

operations.

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 join us!

Key job responsibilities

- Member of a team responsible for system remediation, operational excellence,

and customer experience on bleeding edge ML products

- Utilize data to root cause hardware failures and identify live trends on the

most complex systems in AWS

- Implement and improve system level testing across the product lifecycle

- Develop software which can be maintained, improved upon, documented, tested,

and reused

- Dive deep on issues at the intersection of hardware and software

A day in the life

As a Platform Development Engineer, you are the dedicated owner of an ML server

platform in our fleet. Your mission is to maximize its health, sellability, and

customer experience.

You start each day with eyes on the fleet — reviewing dashboards to identify

trends and triaging emergent issues, then partnering with hardware and software

engineering teams to debug, investigate, and translate findings into permanent

fixes. You own the end-to-end testing story and manage tradeoffs between

coverage and velocity. You direct new automations, tooling, and data

infrastructure to scale your operations. You manage software deployments, debug

issues with them, and run status meetings to align all platform stakeholders on

how the product is performing.

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

• - 2+ years of
• non-internship professional software development experience
• - 1+ years of designing or architecting (design patterns, reliability and
• scaling) of new and existing systems experience
• - 1+ years of administrative experience in networking, storage systems,
• operating systems and hands-on systems engineering experience
• - Knowledge of systems engineering fundamentals (networking, storage, operating
• systems)
• - Experience programming with at least one modern language such as C++, C#,
• Java, Python, Golang, PowerShell, Ruby
• - Experience with Linux/Unix
• - Experience debugging and systems analysis to identify and quickly resolve or
• mitigate issues
• - Bachelor's degree in Computer Science, Computer Engineering, or Electrical
• Engineering

Preferred Qualifications

• - 4+ years of hardware design and
• validation of components, subsystems and systems experience
• - Experience with post-silicon validation
• - Master's degree in Computer Science, Computer Engineering, or Electrical
• Engineering
• 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
• [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
• [https://amazon.jobs/en/benefits].
• USA, TX, Austin - 136,000.00 - 184,000.00 USD annually