Senior AI Engineer

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.

About the role

You will join a dynamic team of propensity modelers dedicated to supporting Verizon's base management organization as it transitions to an agile pod model. As an essential member of this team, you will be assigned to a specific base management pod focused on key moments in the customer lifecycle and specific trigger events. In this role, you will be providing advanced machine learning modeling support that empowers our pods and marketing partners to unlock microsegmentation and high-level personalization, directly driving down customer churn and maximizing lifetime value.

Responsibilities

• Developing, training, and deploying advanced propensity models to predict customer behaviors, churn risk, and lifecycle triggers.
• Collaborating cross-functionally with assigned base management pods to translate complex business problems into actionable data science solutions.
• Unlocking microsegmentation and personalization strategies by translating model outputs into tailored customer journeys for marketing execution.
• Monitoring, evaluating, and refining model performance over time to ensure high accuracy, relevancy, and business impact.
• Partnering with technology and data engineering teams to scale machine learning workflows and production systems.
• Communicating complex analytical concepts and model insights clearly to business partners and executive stakeholders.

Requirements

• Bachelor's degree or four or more years of work experience.
• Four or more years of relevant experience required, demonstrated through work experience and/or military experience.
• Experience building, deploying, and maintaining predictive models or propensity models in a production environment.
• Experience with Python, R, or similar programming languages for data science and machine learning.
• Experience with SQL and database technologies for large-scale data manipulation and extraction.

Qualifications

• Master's degree or Ph.D. in Data Science, Computer Science, Statistics, or a related quantitative field.
• Knowledge of LLMs, RAG, Google ADK, and LangGraph.
• Experience with Google BigQuery.
• Knowledge of base management structures, customer lifecycle stages, or churn prevention strategies.
• Experience working in an Agile environment or within cross-functional, pod-based operating models.
• Experience with cloud platforms such as GCP, AWS, or Azure, and cloud-native machine learning tools (e.g., Vertex AI, SageMaker).
• Experience with machine learning framework ecosystems (e.g., TensorFlow, PyTorch, Scikit-Learn).
• Strong communication skills with the ability to explain complex machine learning models and metrics to non-technical stakeholders.

Schedule

This hybrid role will have a defined work location that includes working from home and a minimum of three days per week in the office, set by your manager. Scheduled weekly hours are 40.

Pay

The annual salary range for this position based on a full-time schedule is $101,000.00 - $194,000.00. This is an incentive-based position with the potential to earn more. For part-time roles, compensation will be adjusted to reflect your hours.

Benefits

• Health and wellness benefit options including medical, dental, vision, short and long-term disability, basic life insurance, supplemental life insurance, AD&D insurance, identity theft protection, pet insurance, and group home & auto insurance.
• Matched 401(k) savings plan.
• Up to 8 company-paid holidays per year and up to 6 personal days per year.
• Paid parental leave, adoption assistance, and tuition assistance.
• Opportunity to receive premium pay such as overtime, shift differential, holiday pay, and allowances.
• Newly hired employees receive up to 15 days of vacation per year, which grows with additional service.