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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.

We are growing and we're hiring people who are inspired by the opportunity to define and build the next generation semiconductor platform.

Key job responsibilities
* Be integrated part of the automation infrastructure team.
* Develop state-of the-art automation infrastructure solution for multiple SW projects.
* Provide solutions which enables automation flows on cloud infrastructure.
* Provide service and support for automation developers.

Required Student Software Engineer - Cloud, Big Data, Billing & AI
What you'll do:
Join a skilled Agile development team building and operating a large-scale cloud platform for our FinOps and Billing.
Develop and enhance cloud-native, distributed systems for collecting, processing, aggregating, and mediating high-volume event data.
Work on backend services and integrations with billing and financial systems, covering the flow from data ingestion and processing to aggregation and billing.
Contribute to Big Data processing pipelines and highly scalable microservices.
Work with databases, event-driven architectures, and messaging and queuing systems.
Develop and improve observability and monitoring capabilities to ensure system reliability, scalability, and performance.
Build AI-powered tools, Model Context Protocol (MCP) integrations, agents, and skills to support system operations, troubleshooting, monitoring, data analysis, and automation.
Explore and apply agentic AI approaches to improve how engineers operate, examination, and interact with complex cloud and Big Data systems.
Develop tools that enable AI agents to query system data, analyze operational information, and assist with day-to-day system management.
Help stabilize, troubleshoot, and improve the performance of production systems.
Improve and optimize development, testing, and operational automation.
Collaborate closely with skilled developers, architects, and domain experts in an international environment.
Gain hands-on experience with modern Cloud, Big Data, DevOps, and AI technologies while working on systems operating at significant scale.