AI Ops Forward Deployment Engineer Intern, BS (2604440)

About Marvell

Marvell’s semiconductor solutions are the essential building blocks of the data infrastructure that connects our world. Across enterprise, cloud and AI, and carrier architectures, our innovative technology is enabling new possibilities. 

At Marvell, you can affect the arc of individual lives, lift the trajectory of entire industries, and fuel the transformative potential of tomorrow. For those looking to make their mark on purposeful and enduring innovation, above and beyond fleeting trends, Marvell is a place to thrive, learn, and lead. 

Your Team, Your Impact

The Employee Experience and Digital Workplace team builds and supports the digital tools and experiences that help Marvell employees collaborate, find information, and work effectively. Day to day, we manage workplace platforms, drive adoption through training and communication, and use employee feedback to keep improving. This removes friction for teams worldwide so they can focus on delivering Marvell’s data infrastructure solutions to cloud, AI, and carrier customers. 
Your internship will focus on AI-assisted IT support and automation. With a mentor, you’ll contribute to a focused project that helps the team detect issues earlier, bring troubleshooting evidence together, or reduce repetitive operational work.

What You Can Expect

• Work with a mentor and IT teammates to understand a practical problem that AI or automation could help solve 
• Build a small script, workflow, or AI-powered prototype with guidance from experienced engineers 
• Explore approved sample tickets, alerts, or knowledge articles to find useful patterns and troubleshooting information 
• Try out relevant AIOps tools and ideas, and share what you learn with the team 
• Help connect approved device-health, meeting-quality, or support signals through APIs, and bring related information together to support troubleshooting 
• Test simple rules for grouping repeated alerts or identifying unusual patterns, and review missed issues and false alarms with your mentor 
• Help improve an AI-assisted troubleshooting workflow by checking its answers against technical evidence, documenting gaps, and proposing changes for engineer review 
• Test your prototype, check whether AI-generated answers are useful and accurate, and improve it based on feedback 
• Follow team guidance on privacy and security, and work in a test environment with engineers reviewing any production changes 
• Present your project back to the team in a clear, practical demo, including what worked and what you learned 

What We're Looking For

• Currently pursuing a Bachelors degree in computer science, computer engineering, information systems, data science, AI/ML, or a related field with an expected graduation date between Fall 2027 – Summer 2028.
• Genuinely passionate about AIOps and eager to build a career applying AI and automation to IT operations.
• Well versed in what’s happening in the AIOps space; actively follows emerging tools, approaches, and use cases, and can discuss examples explored through reading, coursework, technical communities, or personal projects.
• Comfortable writing and debugging basic code in Python, JavaScript, PowerShell, or a similar language; coursework and personal projects count.
• Basic familiarity with REST APIs, JSON, and Git; able to follow documentation to retrieve sample data, inspect a response, and track code changes 
• Hands-on experience with at least one small AI or automation project through coursework, a personal project, or a hackathon; able to explain the problem, your contribution, and how you checked the results 
• Foundational understanding of logs, metrics, and alerts, plus basic device or network troubleshooting concepts such as CPU usage, latency, and packet loss; deep expertise is not expected 
• Basic understanding of how large language models use prompts and retrieved information, including why a convincing answer may still be incorrect 
• Willingness to handle operational data responsibly, protect credentials, use approved tools, and seek guidance before an automation takes action 
• Naturally curious and willing to ask questions, try unfamiliar tools, and learn from feedback 
• Able to explain your work clearly and collaborate with technical and nontechnical teammates 
• Careful and detail-oriented; checks results rather than assuming an AI-generated answer is correct 
• Coursework, personal projects, and hackathons can demonstrate these foundations. Previous internships, professional AIOps experience, production deployment experience, and familiarity with our internal platforms are not required.