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# Distinguished Engineer - ML/AI Engineer

- **Company:** Verizon Communications Inc.
- **Location:** Johns Creek, GA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $137,000.0 - $263,000.0
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, A/B Testing, Artificial Intelligence, Amazon Web Services, Microsoft Azure, Big Data, BigQuery, Information Engineering, R (Programming Language), Python (Programming Language), Machine Learning, Search Technologies, Software Deployment, SQL Databases, Feature Engineering, Pytorch, Retrieval-Augmented Generation, Transfer Learning, Large Language Models, Multi-Agent Systems, Deep Learning, Agentic-AI, Scikit Learn, ONNX (Open Neural Network Exchange) Format, Machine Learning Operations, Agent2Agent Protocol
- **Published:** October 14, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=6e6b8f1042f51151

## About the Role

You are a data science professional who thrives on solving complex analytical problems with minimal guidance. You have a proven track record of managing high-priority machine learning projects, and you excel at collaborating directly with business partners to deliver data-driven customer experiences that impact the bottom line., * 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.
 * 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.

Even better if you have one or more of the following:

 * 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).

## Description

As a Dist Engr-AI Engineer within our team of propensity modelers, you will be responsible for the technical execution of Verizon's transition to a modern, agile pod model. You will work directly at the critical touchpoints of the customer lifecycle and high-impact trigger events, providing the advanced machine learning support needed to unlock deep microsegmentation and hyper-personalization. Your work will directly empower marketers, optimize customer journeys, and drive down churn across our most critical customer segments., * 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., In this hybrid role, you'll have a defined work location that includes working from home and a minimum of three days per week in the office, which will be set by your manager. Employees are responsible for maintaining compliance with hybrid work policies.