Join Annapurna Labs as a Validation Engineer on the Machine Learning Acceleration team, where you'll validate next-generation machine learning accelerators for AWS's cloud infrastructure. This role involves working in a dynamic environment alongside industry experts to tackle complex technical challenges. You will be responsible for ensuring the quality and performance of AI/ML accelerators throughout the product development lifecycle. Your work will span various domains, from low-level hardware interfaces to high-level machine learning workloads.

• Currently has, or is in the process of obtaining a Bachelor’s or Master’s Degree in Computer Science, Computer Engineering, Data Science, Electrical Engineering, or related fields.
• Strong programming skills in two or more of: C/C++, Rust, Go, Python, Lua.
• Familiarity with computer architecture through coursework or projects.
• Experience with Linux environments and Git.
• Experience with system test development, code reviews, source control, build processes, or automated deployments.
• Experience with AWS services or cloud infrastructure.
• Exposure to firmware development including BIOS, BMC, or drivers.
• Validation experience in any of: PCIe, HBM, GPUs, neural networks, ML hardware architecture, and/or CI/CD.
• Familiarity with the validation lifecycle including RTL simulation, emulation, or silicon failure analysis and debug.
• Exposure to Machine Learning hardware or software architecture through coursework or projects.

• Develop comprehensive validation strategies and detailed test plans covering functional, performance, power, and stress testing from silicon bring-up to product release.
• Execute complex test plans from RTL simulation and emulation environments through physical silicon validation.
• Conduct hands-on silicon bring-up and debug in the lab using oscilloscopes, logic analyzers, and protocol analyzers.
• Validate ML accelerator performance, accuracy, and reliability using real-world neural network workloads.
• Build test infrastructure, CI/CD, and automated regression frameworks to enable efficient validation at scale.
• Collaborate across architecture, design, firmware, and software teams to triage failures and drive root cause analysis to closure.
• Review test results, identify patterns, and provide feedback to improve design quality and validation coverage.
• Support production systems in AWS data centers and address field issues as they arise.

• Employees at Amazon are often offered comprehensive health benefits—including multiple medical plan options (no pre-existing condition exclusions, 100% covered in-network preventive care), dental and vision plans, a 24/7 medical advice line from day one, expert second-opinion services, and broad mental-health support with several free counseling sessions (including pediatric). Financial wellness typically includes a 401(k) with company match (up to 2%), Restricted Stock Units (equity), FSAs, an emergency savings program, product and partner discounts, and even college-savings and home-purchase programs. Overall, the package is designed to support employees and their families’ health, finances, and day-to-day life.