AI Infrastructure Engineer Intern

Job description

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 Marvell's CTO Office AI Research Group is looking for a motivated advanced BSc student to join our team as a Data Preprocessing Engineer. You will play a foundational role in building the data infrastructure that powers our AI research — working directly with large-scale, real-world datasets at the intersection of machine learning and semiconductor chip design. This is a hands-on, high-impact student position for someone who enjoys getting into the details of messy data and turning it into clean, structured, and model-ready assets. What You Can Expect Collect, clean, normalize, and sanitize large-scale chip design datasets from diverse sources and formats Build and maintain scripts and pipelines to automate repetitive data extraction and transformation tasks Parse and process a wide variety of file formats (JSON, CSV, Parquet, logs, and domain-specific EDA formats) Navigate complex codebases and directory structures to locate, understand, and extract relevant data Work with structured and semi-structured data using SQL and Python-based tooling Collaborate with researchers and engineers to understand data requirements and deliver model-ready datasets Document data sources, transformation logic, and dataset versions in shared repositories What We're Looking For Advanced BSc student in Computer Science, Software Engineering, Electrical Engineering, Data Science, or a related field Good Python skills with hands-on experience using pandas and NumPy for real data manipulation Solid SQL and comfort working with structured and semi-structured data (JSON, CSV, Parquet, logs) Practical experience cleaning, normalizing, and sanitizing messy, real-world data Comfort navigating codebases and filesystems — understanding directory/file structures and parsing multiple file formats Git fluency — reading commit history, diffs, and working with versioned repositories Scripting ability to automate repetitive extraction and transformation tasks Advantages Exposure to data pipeline tools or frameworks (e.g., Airflow, dbt, Spark) Basic familiarity with ML concepts — understanding what makes a good feature, and awareness of train/test leakage Curiosity for reverse-engineering undocumented data and uncovering hidden relationships across files and datasets Additional Compensation and Benefit Elements With competitive compensation and great benefits, you will enjoy our workstyle within an environment of shared collaboration, transparency, and inclusivity. We’re dedicated to giving our people the tools and resources they need to succeed in doing work that matters, and to grow and develop with us. For additional information on what it’s like to work at Marvell, visit our Careers page. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Interview Integrity To support fair and authentic hiring practices, candidates are not permitted to use AI tools (such as transcription apps, real-time answer generators like ChatGPT or Copilot, or automated note-taking bots) during interviews. These tools must not be used to record, assist with, or enhance responses in any way. Our interviews are designed to evaluate your individual experience, thought process, and communication skills in real time. Use of AI tools without prior instruction from the interviewer will result in disqualification from the hiring process. This position may require access to technology and/or software subject to U.S. export control laws and regulations, including the Export Administration Regulations (EAR). As such, applicants must be eligible to access export-controlled information as defined under applicable law. Marvell may be required to obtain export licensing approval from the U.S. Department of Commerce and/or the U.S. Department of State. Except for U.S. citizens, lawful permanent residents, or protected individuals as defined by 8 U.S.C. 1324b(a)(3), all applicants may be subject to an export license review process prior to employment. #LI-NR1