RAN Automation and Performance Engineering Intern

Job Description

RAN Automation and Performance Engineering Intern | T-Mobile

The Tone:
This is an internship at T-Mobile, located in an in-person setting. T-Mobile is known for innovating and revolutionizing the wireless industry, bringing 5G to the nation and shaping the future of technology. This role offers hands-on experience and training, allowing interns to contribute directly to advancing T‑Mobile’s network technology capabilities within the RAN automation and performance engineering space.

The TL;DR
• Role: Internship
• Type: Temporary (11-week paid learning experience)
• Location: In-person
• Pay: $26–$47 hourly
• Team: Smart Labs, Automation, and Performance team within the National Quality Engineering organization
• Mission: Contribute directly to RAN automation and performance engineering initiatives by developing tools and analyzing data to improve network quality and efficiency.
• Tech Stack: Python, Java, C++, JavaScript, SQL, pandas, machine learning fundamentals, statistical analysis

What You’ll Actually Do
• Software Development: Support the design, development, testing, and deployment of software applications and tools in the RAN automation space.
• Collaboration & Problem Solving: Collaborate with cross-functional teams to assist with data analysis and technical problem-solving.
• Data Analysis: Participate in data mining and analytics, working with both structured and unstructured datasets to uncover patterns, trends, and actionable insights.
• Code Writing: Write clean, scalable, and maintainable code that supports testing and automation workflows.
• Reporting & Presentation: Present project outcomes and key learnings to engineering leadership at the end of the internship.

The Must-Haves
• Background: Actively enrolled in a Bachelor’s or Graduate degree program with an understanding of software development principles, object-oriented programming, and AI/ML concepts.
• Experience: Foundational knowledge of one or more programming languages (e.g., Python, Java, C++, JavaScript) and exposure to data analysis or data mining concepts (e.g., SQL, pandas, machine learning fundamentals, statistical analysis).
• Skills: Strong problem-solving, coding, and analytical abilities, along with effective communication and collaboration skills in a technical team environment.