Distinguished Engineer - ML/AI Engineer

About the role

When you join Verizon You want more out of a career. A place to share your ideas freely — even if they’re daring or different. Where the true you can learn, grow, and thrive. At Verizon, we power and empower how people live, work and play by connecting them to what brings them joy. We do what we love — driving innovation, creativity, and impact in the world. Our V Team is a community of people who anticipate, lead, and believe that listening is where learning begins. In crisis and in celebration, we come together — lifting our communities and building trust in how we show up, everywhere & always. Want in? Join the #VTeamLife.

Responsibilities

• Leading the design, development, and optimization of agentic AI, LLM, and machine learning/deep learning solutions.
• Building, training, and deploying our high-priority propensity models to predict customer behaviors, churn risk, and key lifecycle triggers.
• Drive consolidation of overlapping propensity models into a shared customer state and unified models, reducing operational and development cost.
• Operating independently to manage end-to-end model development pipelines, from advanced feature engineering to production deployment and monitoring.
• Serve as a subject matter expert on agentic development, machine learning and predictive modeling, providing technical guidance and mentorship to junior data scientists.
• Owning the lifecycle of models deployed in high-impact areas, ensuring continuous optimization, accuracy, and measurable business performance.
• Presenting complex model insights, performance metrics, and strategic recommendations clearly to senior leadership and cross-functional business partners.

Requirements

• Bachelor's degree or six or more years of work experience.
• Eight or more years of relevant experience required, demonstrated through work experience and/or military experience.
• Experience working on high-priority or high-visibility technical initiatives within a corporate setting.
• Experience designing and measuring A/B tests or uplift models for targeting.

Skills

• Strong expertise and experience in machine learning/deep learning algorithms, including transformer, transfer learning, NLP, expertise in using Pytorch and scikit-learn packages, as well as probability calibration and time-based validation.
• Experience with Python, R, and SQL for advanced statistical modeling and large-scale data extraction.
• Experience with cloud platforms (e.g., GCP, AWS, or Azure) and production MLOps tools for tracking and maintaining model workflows.

Qualifications

• Knowledge of LLM agent architecture: Google ADK, LangChain/LangGraph, multi-agent orchestration, retrieval-augmented generation RAG, MCP, A2A protocols, ONNX-based embeddings, vector databases and semantic search.
• Knowledge of cloud-scale data engineering: Big Query pipelines, GCP (Cloud Run, Vertex AI).

Schedule

• Hybrid role: defined work location includes working from home and a minimum of three days per week in the office, set by your manager.
• Employees are responsible for maintaining compliance with hybrid work policies.