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Amazon

System Integration Student, Nitro Team, Annapurna Labs

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Annapurna Labs, as part of Amazon, is looking for System Integration Student to join the Nitro cards product team (https://aws.amazon.com/ec2/nitro/).
Our products include the most advanced interfaces and technologies and widely used across AWS data centers as backbone for Nitro and other services. The candidate will own data analysis improving card and server production health and support new servers ramp up in the lab for development and integration purposes.

This role offers hands-on exposure to production-scale server infrastructure, real-world data engineering, and cutting-edge AI/ML integration all within a fast-paced, high-impact hardware program.

Key job responsibilities
As a Student Engineer in the Nitro team, you will assist with data infrastructure across development/production servers and new server integrations in lab environment for accelerator card-to-server platforms. Your work will span three core areas:
- Data Analytics & Dashboards — Build and maintain databases and dashboards that track manufacturing and production metrics for servers in fleet, including yield, first-pass rate, cycle time, and defect analysis. You will work with real production data to generate actionable insights that drive process improvements and support decision-making across the integration team.
- AI-Powered Data Capabilities — Assist in ramping the team's AI capabilities by incorporating machine learning and automation into data analysis workflows and database operations from anomaly detection and trend analysis to intelligent alerting and predictive insights that accelerate issue identification and resolution.
- New Server Integration & Lab Support — Support the integration of new server platforms by assisting with lab ramp-up activities, including server bring-up, firmware and hardware issue triage, quick-turn debug cycles, and development environment readiness. You will work alongside experienced engineers to help accelerate the path from first power-on to stable, repeatable operation.

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