From Astera Labs’s careers page.
Packaging Automation & Data Engineering Intern
Location: San Jose, California, United States
Employment type: Internship
Organization: Packaging / Engineering Operations
About Astera Labs
Astera Labs is a semiconductor company developing intelligent connectivity solutions for AI and cloud infrastructure. Our products depend on high-performance interconnects and advanced semiconductor packaging to move data reliably across compute, memory, and storage systems.
Role overview
As a Packaging Automation & Data Engineering Intern, you will be part of the packaging team developing Astera Labs’ portfolio of connectivity products for leading cloud service providers and server and networking OEMs. You will focus on software tools, scripting, data pipelines, and databases that improve engineering efficiency, data quality, traceability, and decision-making across package development and manufacturing.
You will work closely with packaging engineers and cross-functional teams to translate engineering workflows into reliable software solutions. This is a hands-on role for someone who enjoys coding, structuring engineering data, automating repetitive tasks, and building practical tools for real engineering problems. You will have opportunities to work with package design data, manufacturing and qualification information, supplier inputs, and engineering analysis results.
Responsibilities
- Develop Python-based scripts and applications to automate packaging engineering workflows, data processing, file handling, report generation, and repetitive engineering tasks.
- Collaborate with packaging engineers to understand manual workflows, identify automation opportunities, define requirements, and develop maintainable software solutions.
- Build tools to extract, clean, transform, validate, and consolidate engineering data from sources such as Excel, CSV, TXT, HTML, PDF-derived datasets, and structured design or manufacturing files.
- Design and maintain structured databases or data repositories for package, substrate, assembly, qualification, supplier, and manufacturing information, with attention to data integrity and traceability.
- Develop scripts and utilities to compare package design information, BOMs, design rules, material properties, supplier capability data, and other engineering datasets.
- Create automated checks and review tools that flag missing information, inconsistencies, out-of-spec conditions, or potential design and manufacturing risks.
- Develop internal engineering applications or lightweight GUIs/web tools that allow engineers to run automation flows, review results, and provide user inputs efficiently.
- Support data visualization and dashboard development for engineering metrics, NPI status, qualification results, supplier capability, manufacturing data, or other packaging-related information.
- Integrate data from multiple sources and help establish reusable data pipelines, naming conventions, schemas, version control, and documentation practices.
- Support automation involving package geometry or design data, including processing information from package drawings, layout exports, DXF files, netlists, or other structured engineering formats when applicable.
- Apply software-engineering practices such as modular code design, error handling, logging, validation, testing, and source control to improve reliability and maintainability of engineering tools.
- Help improve existing scripts and engineering tools by debugging issues, optimizing performance, refactoring code, and adding new capabilities based on user feedback.
- Prepare clear documentation for scripts, databases, data structures, workflows, assumptions, and user instructions so solutions can be maintained and reused by the team.
- Support communication with internal engineering teams, substrate suppliers, and OSAT partners when data collection, standardization, or automation interfaces are required.
- Present completed projects, technical approach, results, and measurable efficiency or quality improvements at the end of the internship.
Basic qualifications
- Working towards a B.S., or M.S. in Computer Science, Computer Engineering, Electrical Engineering, Data Science, Mechanical Engineering, or a related technical field.
- Cumulative GPA of 3.2/4.0 or higher.
- Entrepreneurial, open-minded behavior and a hands-on work ethic, with the ability to prioritize a dynamic list of multiple tasks.
- Ability to work with minimal supervision and deliver solutions in a fast-paced environment.
- Strong time-management skills and strong written and verbal communication skills.
Required experience
- Coursework or project experience in programming, data structures, databases, software engineering, data analytics, or engineering computation.
- Strong programming experience in Python; experience with common data-processing libraries such as pandas, NumPy, or equivalent tools.
- Experience working with structured data and databases, including SQL and relational database concepts.
- Experience developing scripts or software for automation, data processing, file parsing, analysis, or engineering applications.
- Strong analytical and problem-solving skills, with careful attention to data quality, edge cases, validation, and reproducibility.
- Ability to communicate clearly, collaborate with engineers from different disciplines, and translate engineering requirements into practical software solutions.
Preferred experience
- Experience with Python GUI or web-application frameworks such as PyQt/PySide, Streamlit, Flask, FastAPI, or comparable tools.
- Experience with SQL databases such as SQLite, PostgreSQL, MySQL, or similar platforms, including schema design, queries, and data integration.
- Experience with Git or other version-control systems and familiarity with collaborative software-development practices.
- Experience with data visualization or dashboard tools such as Plotly, Power BI, Tableau, Matplotlib, or similar tools.
- Experience parsing or generating engineering file formats and automating Microsoft Excel or other office workflows using Python, APIs, or similar methods.
- Familiarity with APIs, ETL/data pipelines, REST services, cloud databases, or data-management platforms is a plus.
- Exposure to machine learning, computer vision, large-language-model applications, or AI-assisted engineering workflows is a plus.
- Understanding of semiconductor packaging, electronics manufacturing, package design, FCBGA/FCCSP, substrate technology, or OSAT workflows is a plus but not required.
- Experience developing software or automation for engineering, laboratory, manufacturing, research, or hardware-related applications.
- Prior internship, research, coursework, or personal projects demonstrating ownership of a software, database, automation, or data-analysis project from problem definition through implementation.
What success looks like
- You learn the packaging team’s engineering workflows and data environment, then take ownership of one or more automation or data-engineering projects with appropriate guidance.
- You deliver reliable, documented, and reusable code or database solutions that reduce manual work, improve data quality, or make engineering information easier to access and analyze.
- By the end of the internship, you have deployed or demonstrated useful tools for scripting, data processing, database management, engineering review automation, or visualization and can clearly explain the problem, architecture, implementation, validation, and impact.
Internship experience and compensation
This is a paid, hourly U.S. internship. The applicable hourly rate is determined as part of the offer process and specified in the offer letter, depending on education level ranges from $35/hour to $55/hour. U.S. interns currently receive a $500-per-week housing/relocation stipend for the duration of the internship. Interns participate in Early Career programming, including technical and professional-development sessions, community events, and an end-of-program project presentation.
Equal opportunity
Astera Labs is an equal opportunity employer committed to fostering a diverse and inclusive workplace. We encourage anyone with relevant experience to apply.
