Intern

Summary: Initiates the design, development, execution and implementation of technology research projects. Investigates the feasibility of applying scientific principles and concepts to potential inventions and products. Plans and executes applied research. Maintains substantial knowledge of state-of-the-art principles and theories, and may contribute to scientific literature and conferences. May participate in development of patent applications. May coordinate interdepartmental activities and research efforts. Duties & Responsibilities: Join the CTO Innovation Center at VIAVI Solutions to learn and develop next-generation AI software applications on top of industry-leading telecom test platforms. This internship provides hands-on experience in combining AI/ML technologies with wireless and optical network testing, AI-RAN validation, digital twin environments, and network traffic emulation. Unlike conventional software internships, this role exposes students to cutting-edge domains including AI-driven network automation, RAN digital twins, etc. Key Responsibilities Learn and develop AI-enabled software modules integrated with VIAVI test platforms Implement Python-based backend services and APIs Develop web-based UI/dashboard components for monitoring and analytics Work with telecom datasets such as RAN (Radio Access Network) KPIs, UE mobility simulations, etc. Contribute to technical documentation, demonstrations, and presentations Month 1 — Requirement Study & Environment Setup Objectives Understand Digital Twin architecture and workflows Learn telecom digital twin concepts Define application scope and technical architecture Activities Study Digital Twin APIs and scenario configuration Review existing mobility, traffic, and UE simulation features Setup development and test environment Deliverables Development environment ready Requirement specification document High-level application architecture diagram Initial proof-of-connectivity to Digital Twin APIs Month 2 — Core Framework Development Objectives Build core backend framework and data pipeline Activities Develop backend services/API modules Implement Digital Twin scenario management functions Build data ingestion and telemetry collection modules Create database/storage structure for scenario metadata Deliverables Working backend framework Digital Twin control interface prototype Scenario configuration parser Initial telemetry collection pipeline Month 3 — AI & Automation Feature Development Objectives Introduce AI-assisted intelligence and automation Activities Develop AI-based scenario recommendation engine Implement anomaly detection or KPI prediction models Build automation workflows for scenario generation Enable AI inference traffic orchestration Deliverables AI-assisted scenario generation prototype Basic ML model integration Automated test workflow execution Technical demonstration to mentor team Month 4 — Frontend Dashboard & Visualization Objectives Build user-facing dashboard and visualization capabilities Activities Develop web UI/dashboard Visualize UE movement, traffic patterns, and KPIs Add monitoring and analytics capabilities Implement real-time scenario status tracking Deliverables Interactive dashboard prototype Real-time KPI visualization Digital Twin scenario monitoring page User workflow demonstration Month 5 — Advanced Integration & Optimization Objectives Integrate multi-domain workflows and optimize performance Activities Optimize backend performance and scalability Validate large-scale crowd/mobility simulations Conduct stress and performance testing Deliverables End-to-end integrated prototype Performance benchmark report Multi-domain orchestration workflow Stability and scalability improvements Month 6 — Final Validation & Demonstration Objectives Finalize application and demonstrate business/technical value Activities Conduct final validation testing Prepare demonstration scenarios Document architecture and implementation details Present outcomes to CTO leadership/research partners Deliverables Final Digital Twin application prototype Complete technical documentation Final presentation/demo including: Architecture overview AI workflow Key innovations Performance results Future roadmap suggestions Pre-Requisites / Skills / Experience Requirements: Required Preferred Skills & Qualifications Currently pursuing Bachelor’s, Master’s, or PhD in: Computer Science Electrical Engineering Telecommunications AI / Machine Learning Data Science Programming experience in Python Familiarity with REST APIs and Linux environments Preferred Knowledge of: Machine Learning / Deep Learning frameworks LLMs or AI agents Data analytics and visualization