Software Design Engineer Intern for Physical Design

Description

Job Details:

Responsibilities

• As an AI/ML Software Engineering Graduate Intern, you will contribute to the design, development, and optimization of cutting-edge AI solutions for semiconductor design and engineering workflows. Working at the intersection of Artificial Intelligence/Machine Learning (AI/ML), Electronic Design Automation (EDA), and software engineering, you will research and prototype intelligent solutions that enable smarter design flows, accelerate automation, and improve engineering efficiency.
• You will gain hands-on experience developing and tuning ML models, exploring Agentic AI and autonomous workflows, and integrating AI capabilities into scalable engineering and production environments.
• Business group
• You will be joining the Central Engineering Group (CEG), a dynamic team that drives the company's engineering excellence across diverse domains. This organization focuses on creating innovative solutions that support the company's global business goals, with an emphasis on collaboration, technical expertise, and impactful projects. As part of the team, you'll have the opportunity to contribute to the company's mission of shaping the future of technology.
• Research, design, and prototype AI/ML-driven solutions for semiconductor and EDA challenges.
• Develop, implement, and optimize AI/ML models for performance, accuracy, and engineering efficiency.
• Explore advanced AI techniques, including Agentic AI, to create autonomous and intelligent engineering workflows.
• Develop software frameworks, automation, and AI-enabled solutions that support scalable engineering workflows.
• Collaborate with global product and engineering teams to integrate AI/ML capabilities into production workflows.
• Support applied research, hardware-software integration, and system-level deployment of AI technologies.
• Analyze experimental results and identify opportunities to improve AI models, design flows, and automation.
• Gain hands-on experience across AI/ML, software engineering, EDA, and semiconductor design.

Requirements

• Minimum qualifications are required to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.
• Minimum Qualifications:
• Currently pursuing a Master's degree OR PhD in Electrical Engineering, Computer Engineering, Computer Science or any related field.
• Solid understanding of AI/ML fundamentals and algorithms.
• Strong programming skills in Python (preferred), with familiarity in Unix/Linux.
• Good understanding of software engineering principles (data structures, object-oriented design).
• Excellent communication skills and fluency in English.
• Preferred Qualifications:
• Knowledge of ASIC design flows, Physical Design, and Design Automation.
• Practical experience applying Machine Learning in EDA or related domains.
• Familiarity with Agentic AI concepts and ability to design autonomous flows.
• Strong foundation in VLSI Design.
• Good code development practices and ability to write clean, maintainable code.
• Requirements listed would be obtained through a combination of industry relevant job experience, internship experiences and or schoolwork/classes/research.
• Job Type:
• Student / Intern
• Shift:
• Shift 1 (Germany)
• Primary Location:
• Germany, Munich
• Additional Locations:
• Posting Statement:
• Position of Trust
• N/A
• EU Salary
• We offer a total compensation package that ranks among the best in the industry.
• The minimum Annual Salary for this job which could be performed in Germany is: 28 920,00 €
• The job posting reflects the minimum base compensation for this role. Our standard internship rates are aligned with the specific job role and degree level. As part of our total compensation approach, the final offer may also include additional pay components and benefits. Your recruiting team will provide the confirmed base salary along with any applicable total compensation elements upon employment offer delivery.
• Work Model for this Role
• This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned the company site and off-site. Job posting details (such as work model, location or time type) are subject to change.