Wireless Network Lab Intern

VIAVI Solutions • Chandler, AZ

1d

About The Position

VIAVI (NASDAQ: VIAV) is a global provider of network test, monitoring and assurance solutions for telecommunications, cloud, enterprises, first responders, military, aerospace, and railway. VIAVI is also a leader in light management technologies for 3D sensing, anti-counterfeiting, consumer electronics, industrial, automotive, government and aerospace applications. We are the people behind the products that help keep the world connected at home, school, work, at play, and everywhere in between. VIAVI employees are passionate about supporting customer success and we welcome people who bring their best every day to the company – to question, to collaborate and to push for solutions that will delight our customers.

Requirements

• Currently pursuing a Ph.D. (or advanced M.S.) in Electrical Engineering, Computer Science, or a related field.
• Research focus in machine learning, with hands-on experience in deep learning frameworks (PyTorch or TensorFlow).
• Experience training and fine-tuning large-scale models.
• Strong Python proficiency and familiarity with GPU-accelerated workflows.
• Track record of research output (publications, preprints, or significant thesis work).
• Ability to work independently on open-ended research problems in a collaborative team environment.

Nice To Haves

• Experience with foundation models, large language models, or domain adaptation techniques.
• Familiarity with parameter-efficient fine-tuning methods (LoRA, adapters, or similar).
• Background in wireless communications, signal processing, or telecom systems.
• Experience with retrieval-augmented generation (RAG) or knowledge-grounded AI systems.
• Prior industry research internship experience

Responsibilities

• Design and develop AI/ML models tailored to telecom operational use cases, including diagnostics, protocol analysis, and test automation.
• Build and manage data pipelines — curate, clean, and structure training datasets from diverse telecom sources.
• Run training experiments on GPU infrastructure and iterate on model performance.
• Develop evaluation benchmarks and validate model outputs against domain expert assessments.
• Collaborate with cross-functional engineers (RF, RAN, security, software) to translate domain expertise into model capabilities.
• Contribute to a research publication documenting methodology and results.

What This Job Offers

• Career Level: Intern
• Education Level: Ph.D. or professional degree
• Number of Employees: 501-1,000 employees