Post-Silicon Systems Validation Engineer, Annapurna Labs
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—to deliver exceptional results.We Are Looking For Candidates With
- Strong programming skills (Python, Lua, C/C++, Rust, Go, etc)
- A solid understanding of computer architecture
- Experience with AWS services, cloud infrastructure, firmware development (BIOS, BMC, drivers)
- Validation experience in any of these areas: PCIe, HBM, GPUs, neural networks, ML HW architecture, and/or CI/CD
- Familiarity with the validation lifecycle from RTL simulation (SystemVerilog/UVM, VCS, Questa, Xcelium) and emulation (Palladium, Zebu, Veloce) through silicon failure analysis and debug
- Developing comprehensive validation strategies and detailed test plans covering functional, performance, power, and stress testing from silicon bring-up to product release
- Executing complex test plans from RTL simulation and emulation environments through physical silicon validation
- Conducting hands-on silicon bring-up and debug in the lab using oscilloscopes, logic analyzers, and protocol analyzers
- Validating ML accelerator performance, accuracy, and reliability using real-world neural network workloads
- Building test infrastructure, CI/CD, and automated regression frameworks to enable efficient validation at scale
- Collaborating across architecture, design, firmware, and software teams to triage failures and drive root cause analysis to closure
- Reviewing test results, identifying patterns, and providing feedback to improve design quality and validation coverage
- Supporting production systems in AWS data centers and addressing field issues as they arise
- Experience with general troubleshooting/debugging of hardware, or experience in computer architecture
- 3+ years of non-internship system test development, code reviews, source control management, build processes, automated deployments, and operations experience.
- Experience with Linux environments and Git.
- Experience with Machine Learning Hardware/Software Architecture
- Experience with CI/CD
- Experience with EDA Simulations or Emulation
