Working Student - Forward Deployed Engineer iv

Infineon Technologies AG
München, Germany
2 months ago
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Role details

Contract type
Temporary contract
Employment type
Part-time (≤ 32 hours)
Working hours
Regular working hours
Languages
English, German
Job source

Tech stack

Clean Code Principles Artificial Intelligence Code Review Python (Programming Language) Machine Learning NumPy Pytorch Large Language Models Git Fastapi Pandas Scikit Learn
+3 more
Information Technology Streamlit Framework Automation Anywhere

Job description

The future won’t wait… why should you? Join us and make a difference. Whether you join as a student, intern, or trainee, you’ll be part of something real - real projects, real impact, and real opportunities to grow.

Are you in?

Your role

This role involves designing, developing, and evaluating AI workflows and tools, as well as contributing to the creation of reusable resources and supporting integration with larger platforms., Keep the overview: Work on AI projects from start to finish, designing and implementing tools and workflows, with guidance from the team, to create tested prototypes

  • Reliable work: Building and evaluating workflows, designing prompts and tools, and creating robust error handling mechanisms, as well as developing evaluation setups to test the quality of the workflows
  • Take responsibility: Developing and prototyping machine learning models for reliability and quality analytics, such as outlier detection and predictive models, and packaging the results in a reproducible manner
  • Expand your horizons: Contribute to creating a reusable “starter kit” with templates and documentation, and support the integration of the AI workflows into larger platforms by producing clear interfaces, tests, and documentation, * Working part-time: The focus is on studies. That’s why working as a student employee during lecture period is limited to a maximum of 20 hours per week.
  • Proper students (according to the German law) are welcome: To work as a student employee with us, you must be enrolled at a university and not have completed all of your exams or modules for your degree programme. You must not be in a semester of leave. We look forward to welcoming you to our team for at least 6 months.
  • You should live close to the site: For good collaboration, it is important to us that you can come to the office regularly to integrate to the team.

WeAreIn for driving decarbonization and digitalization.

As a global leader in semiconductor solutions in power systems and IoT, Infineon enables game-changing solutions for green and efficient energy, clean and safe mobility, as well as smart and secure IoT. Together, we drive innovation and customer success, while caring for our people and empowering them to reach ambitious goals. Be a part of making life easier, safer and greener. Are you in?

We are on a journey to create the best Infineon for everyone.

We strive to create the best Infineon for everyone by embracing diversity and inclusion. We welcome applicants for who they are and offer a workplace built on trust, openness, respect and equal opportunity.

Requirements

  • Study field: Enrolled in a Master’s program (or advanced Bachelor) in Computer Science, Data Science, Physics, Electrical Engineering or similar
  • Skills:

o Have strong Python skills (pandas/NumPy), and ideally first experience with FastAPI/Streamlit or building small services

o Comfortable with Git, code reviews, and writing maintainable code (tests are a plus)

o Understand basic ML concepts (train/test split, metrics, overfitting); PyTorch/scikit-learn experience is a plus

  • Experience: First hands-on experience with LLMs/agents (prompting, tool calling, evaluation) and are motivated to go deeper
  • Way of working: You can work independently on ambiguous tasks (clarify requirements, propose options, and drive to a result), and can collaborate with engineers and domain experts
  • Language skills: You are fluent in English (German is a plus)

Please attach the following documents to your application:

  • CV in English
  • Certificate of enrollment at university
  • Latest grades transcript (not older than 6 months)
  • High school report

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