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Apple

Internship - Software Engineering - Wireless Data Science

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Summary

Internship on Apple's Wireless Technologies & Ecosystems team in Munich, developing software to mine and analyze 4G/5G cellular data. The intern builds agentic workflows and data/ML-powered wireless features using Python, data engineering pipelines, and machine learning to improve product quality and customer experience.

Wireless Technologies & Ecosystems (WTE) team is looking for an intern with passion for SW Development, Data Engineering, Statistical Analysis and Machine Learning, all applied to 4G/5G cellular domains. Our team develops and maintains solutions for mining cellular data and performance metrics to improve overall product quality and customer experience. We are a multidisciplinary team covering different competences including cellular engineering, data pipelining, data engineering, data science, data analytics, software development and machine learning. If you’re passionate about SW engineering, data analytics and applying ML models on crowd source data, then we have the job for you.

Developing SW solutions to enhance data analytics capabilities by addressing data collection pain points and providing solutions to optimise wireless/cellular communication. The ideal candidate will design & develop agentic workflows, as well as Data & AI/ML powered wireless features.

Minimum Qualifications

  • M.S. or PhD in Computer/Electrical Engineering, Computer Science/Informatics or equivalent.
  • Solid knowledge and hands-on experience designing and implementing agentic workflows and multi-agent systems
  • Solid software engineering skills in a multi-language environment (Python is a must, ObjectiveC, Swift and Java are optional)
  • Experience with data mining / data analysis and data visualization
  • Experience in applying machine learning algorithms to understand real-world data, data collection, model training & model evaluation

Preferred Qualifications

  • Experience in developing applications for iOS
  • Knowledge in database and data manipulation (SQL), as well as experience with time series analysis to discover patterns over time
  • Good understanding of cloud methodologies
  • Ability to quickly learn new development environments and APIs
  • Comfortable with quick context switching between several projects
  • Excellent debugging and problem solving skills
  • Team player

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