Annapurna Labs
Technology
Post-SiliconSystemsValidationEngineer
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Post-Silicon Systems Validation Engineer at Annapurna Labs. Skills: Silicon validation, Machine Learning accelerators, Hardware design, Software development. Own validation aspects. Validate next-generation accelerators”
Industry & Context.
Root cause analysis
What They're Looking For.
Must Have
Programming with at least one language, 3+ years system design experience, Machine Learning fundamentals experience, Large Language Model fundamentals experience, Experience with PyTorch or JAX, Bachelor's degree in CS, engineering, math, Experience debugging large-scale systems, Experience profiling large-scale systems, Experience implementing software engineering best practices, Experience in development in the last 3 years, Understanding of computer architecture fundamentals, Experience applying statistical methods, Experience applying regression analysis, Experience applying data visualization techniques
Nice to Have
3+ years full SDLC experience
What You'll Do.
Own validation aspects
Validate next-generation accelerators
Develop validation strategies
Develop detailed test plans
Execute complex test plans
Conduct silicon bring-up
Conduct silicon debug
Validate ML accelerator performance
Validate ML accelerator accuracy
Validate ML accelerator reliability
Build test infrastructure
Build automated regression frameworks
Drive root cause analysis
Support production systems
How You'll Work.
Team & Collaboration
Architecture teams; RTL design teams; Design verification teams; Firmware teams; Software teams
Process & Methodology
CI/CD
Full Job Description
Annapurna Labs, an AWS organization with development centers in the U.S. and Israel, builds custom silicon and software for AWS customers. Our team combines cloud-scale innovation with world-class expertise across silicon engineering, hardware design, verification, software, and operations to tackle technical challenges that have never been seen before. Join our Silicon Validation team to validate next-generation machine learning accelerators that power AWS's cloud computing infrastructure. You'll work in a fast-paced, startup-like environment alongside some of the brightest minds in the industry on cutting-edge, internet-scale technology that directly impacts how customers use Machine Learning acceleration. We are changing the landscape of cloud infrastructure by accelerating the development of custom silicon by moving beyond traditional partnerships to dominate in AI training and inference Your work will span validation of the complete vertical stack—silicon, PCB, high-speed components (HBM, PCIe, chip-to-chip), inter-system connections, and system-to-system interfaces. You'll dive deep into new technology hardware components and scaling technologies that power our Machine Learning boards and servers at scale, ensuring every component of our hardware and software comes together into products our customers rely on. Key job responsibilities As a Validation Engineer on our Machine Learning Acceleration team, you'll own critical validation aspects across the entire product development lifecycle—from early design validation through emulation, silicon bring-up, post-silicon validation, and ongoing support of production systems deployed in AWS data centers. You'll collaborate deeply with architecture, RTL design, design verification, firmware, and software teams to ensure our next-generation AI/ML accelerators meet the highest standards of quality and performance. This role requires bridging multiple domains—from low-level hardware interfaces to high-level ML workloads—t
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