Jobs at Verizon

Provides centralized 24/7 troubleshooting and operational support for Verizon’s wireless network. Responsibilities include monitoring network events, performing fault isolation and remediation, creating trouble tickets, escalating issues, communicating with internal and external customers, and supporting network availability during outages. The role includes training and development in LTE, 4G/5G, cloud, virtualization, scripting, and telecommunications technologies.

Design and build predictive and prescriptive models (churn, segmentation, survival, forecasting), run experiments (A/B, multi-armed bandit), deploy cloud-based solutions (PySpark on AWS/GCP), synthesize insights, and collaborate cross-functionally to inform marketing, finance, and operations decisions.

Design, develop, and optimize AI, SLM/LLM, and agentic solutions. Implement and tune algorithms and large-scale distributed training, orchestrate model fine-tuning and serving, analyze performance, define APIs, and communicate technical outcomes to non-technical stakeholders.

Design, productionize, optimize, and deploy large-scale AI and machine learning models and infrastructure. Build distributed training and inference systems, resilient data pipelines, evaluation suites, monitoring, logging, and ML CI/CD workflows. Collaborate with research, data, and platform engineers to turn prototypes into scalable, low-latency applications. Provide technical leadership through code reviews, mentoring, and engineering best practices.

Lead technical pre-sales for mid-to-large enterprise deals: perform discovery, whiteboard solutions, scope automation, design scalable SD-WAN/cloud network architectures, validate BOMs/RFPs, mentor junior architects, and align Sales, Delivery, and Product.

Lead advanced threat-hunting missions, investigate cyber threats and insider misconduct, develop IOCs and IOAs, analyze cloud and security data, improve detection and incident-response capabilities, support digital forensics, participate in purple-team exercises, present executive metrics, and mentor cybersecurity team members.

Leads the architecture, development, and deployment of large-scale AI/ML, generative AI, and agentic systems. Responsibilities include designing end-to-end ML pipelines, fine-tuning and evaluating LLMs, mentoring data science and engineering teams, establishing secure and ethical AI practices, and providing technical thought leadership. The role also covers model monitoring, MLOps, distributed infrastructure, conversational data analysis, cross-functional collaboration, and adoption of emerging AI technologies.

Build and govern LookML semantic layers, Explores, derived tables, and metrics for dashboards and conversational analytics. Develop high-performance SQL and BigQuery data models, validate data, and create Looker dashboards. Connect LLM-based query tools and AI assistants to governed data sources, contribute to agentic analytics workflows, and collaborate with business stakeholders on consumer behavior, churn, and revenue analysis.

Leads architecture, development, deployment, and optimization of large-scale AI/ML, generative AI, and agentic systems. Oversees data pipelines, model training, monitoring, validation, and lifecycle practices while mentoring data science and engineering teams. Partners with product and business stakeholders, establishes secure and ethical AI standards, analyzes conversational data, evaluates emerging technologies, and provides technical thought leadership on scalable model architectures and MLOps.

Develops agentic AI solutions, statistical models, optimization methods, dashboards, and actionable analytics for supply chain and operations. Builds and validates models using large-scale data, integrates LLM APIs and agentic frameworks, ensures data quality, and translates business problems into analytical solutions. Partners with data scientists, engineers, and stakeholders to deliver production-grade AI products and communicate business implications.

Build, deploy, and manage end-to-end AI services for traditional and generative AI use cases. Design scalable AI/ML solutions, distributed computing systems, training and deployment pipelines, and advanced algorithms. Analyze and optimize model performance across cloud platforms, GPUs, containers, and serving platforms while collaborating with cross-functional teams to deliver business-focused solutions.

Leads the architecture, development, and deployment of large-scale AI/ML, generative AI, and agentic systems. Responsibilities include designing data pipelines and model architectures, fine-tuning and evaluating LLMs, mentoring AI teams, establishing MLOps and validation best practices, ensuring secure and ethical deployments, and partnering with product and business stakeholders. The role also provides technical thought leadership, analyzes conversational data, and drives scalable AI innovation.

Develop and maintain Python automation scripts for the Wireless Network Management Center. Analyze wireless trouble tickets and alarms to identify trends and business impact, interpret worklog entries, understand automation workflows, and answer user questions. The role also involves troubleshooting complex problems, supporting large-scale IT systems and applications, collaborating with stakeholders, and adapting code to new scripting languages in a hybrid work environment.