Data Intake and Machine Learning Intern
vor 1 Woche
About Munich Re
Munich Re is the world's leading reinsurance company, with over 11,000 employees at more than 50 locations. We turn uncertainty into manageable risk, enabling fundamental change. Our work focuses on topics that will concern society tomorrow, such as climate change, major construction projects, medical risk assessment, and space travel.
Our Culture
We cultivate innovation and create the new and the different for our clients. Our multiskilled teams dare to think big, embracing a culture where diversity fosters innovation and resilience. We believe that diversity, equity, and inclusion are key to our success.
What We Offer
- Diversity, Equity & Inclusion: We value the power of differences and believe it enables us to act braver and better.
- Continuous Learning: We offer opportunities for continuous learning, building new skills, and accelerating growth.
- Career Mobility: We support career mobility, with a global and regional presence offering a wealth of career growth opportunities.
Your Role
As a Data Intake and Machine Learning Intern, you will be part of a team that develops production-grade ETL pipelines and machine learning models. You will collaborate with highly qualified data science and software professionals to ship production-grade functionality. Your responsibilities will include:
- Developing production-grade ETL pipelines hands-on.
- Developing machine learning models and prompts used in the broader field of data intake.
- Collaborating with a team to ship production-grade functionality.
Your Profile
We are looking for candidates with a strong background in computer science, electrical engineering, or a related field. You should have hands-on experience with machine learning, data processing, and large language models. Familiarity with software development patterns such as CI/CD and SCRUM is also required.
Requirements
- Study in computer science, electrical engineering, or a related field.
- Strong Python skills.
- Hands-on experience with machine learning, data processing, and large language models.
- Familiarity with software development patterns such as CI/CD and SCRUM.
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