RAN Automation and Performance Engineering Intern

Job Description

RAN Automation and Performance Engineering Intern | T-Mobile

The Tone:
This is an 11-week paid internship at T-Mobile, located in Herndon, VA. T-Mobile is known for its role in disrupting the wireless industry, reinventing customer service, and bringing 5G technology to the nation. This role is crucial for contributing to the Smart Labs, Automation, and Performance team, which advances T-Mobile’s network technology capabilities through automation, performance evaluation, and deep data analysis within the RAN space. The work directly impacts the company’s ability to innovate and maintain its technological edge.

The TL;DR
• Role: Internship
• Location: Herndon, VA
• Pay: $26–$47 hourly
• Team: Smart Labs, Automation, and Performance team within the National Quality Engineering organization
• Mission: To contribute directly to RAN automation and performance engineering initiatives by supporting software development, data analysis, and innovative system enhancements.
• Tech Stack: Python, Java, C++, JavaScript, SQL, pandas, machine learning fundamentals, statistical analysis, AI/ML concepts

What You’ll Actually Do
• Develop: Support the design, development, testing, and deployment of software applications and tools in the RAN automation space.
• Analyze: Collaborate with cross-functional teams to assist with data analysis and technical problem-solving across diverse testing environments.
• Mine Insights: Participate in data mining and analytics, working with structured and unstructured datasets to uncover patterns, trends, and actionable insights.
• Code: Write clean, scalable, and maintainable code that supports testing and automation workflows, including tools for data structuring, visualization, and reporting.
• Innovate: Apply AI-based analysis and contribute innovative ideas to enhance existing systems, processes, and services for increased efficiency in post-processing, log evaluation, and automated insights.

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