Annapurna Labs
Technology
AIHardwareSystemsEngineer
Neural analysis suggests this role is
optimal for Mid+ candidates.
“AI Hardware Systems Engineer at Annapurna Labs. Skills: ML hardware, Fleet operations, System debugging. Debug emergent problems. Write scripts”
Industry & Context.
Root cause analysis; Debugging; Systems analysis
What They're Looking For.
Must Have
2+ years software development experience, 1+ years system design/architecture, 1+ years systems engineering experience, Systems engineering fundamentals knowledge, Experience with Linux/Unix, Experience debugging and systems analysis, Bachelor's degree in CS, CE, or EE
Nice to Have
Experience in hardware design, Experience with SOC bring-up, Master's degree
What You'll Do.
Debug emergent problems
Run large scale experiments
Develop data infrastructure
Develop automation software
Monitor machine learning hardware
Optimize machine learning hardware
Remediate machine learning hardware
Root cause hardware failures
Implement system level testing
Improve system level testing
Develop maintainable software
Develop improvable software
Develop documented software
Develop testable software
Develop reusable software
Maximize server health
Maximize server sellability
Maximize customer experience
Triage emergent issues
Partner with engineering teams
Translate findings into fixes
Own end-to-end testing
Manage testing tradeoffs
Direct new automations
Direct data infrastructure
Manage software deployments
Debug software issues
How You'll Work.
Team & Collaboration
Hardware engineering teams; Software engineering teams
Full Job Description
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 fl
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