AI Hardware Systems Engineer, Annapurna Labs, Trainium Machine Learning Fleet Operations; AWS

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!

• 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 that can be maintained, improved upon, documented, tested, and reused
• Dive deep on issues at the intersection of hardware and software

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.

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.

• 2+ years of non‑internship professional software development experience
• 1+ years of designing or architecting new and existing systems (design patterns, reliability and scaling)
• 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, Power Shell, 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

• Experience in hardware design and validation of components, subsystems and systems
• Experience with SOC bring‑up and post‑silicon validation
• Master's degree in Computer Science, Computer Engineering, or Electrical Engineering

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