Distinguished Engineer - AI/ML Engineering

When you join Verizon you’ll find a place to share daring ideas, learn, grow, and thrive while powering how people live, work, and play. Our V Team anticipates, leads, and believes that listening is where learning begins, building trust and lifting communities everywhere.

Responsibilities

• Device‑Side AI & Telemetry: Design, engineer, and deploy edge‑side telemetry pipelines and AI/ML models on devices to collect, process, and analyze real‑time performance signals, counters, and event logs.
• Agentic AI & Digital Employees: Architect and operationalize GenAI‑powered agents, LLMs, retrieval‑augmented generation (RAG), and agentic frameworks to function as digital employees capable of proactive troubleshooting, root‑cause analysis, and automated decision‑making.
• Multi‑Cloud & Data Architecture: Build and scale data analytics and streaming pipelines across AWS and GCP to handle high‑throughput network and device telemetry.
• Autonomous Network Enablement: Drive proactive fault detection, anomaly detection, and closed‑loop remediation workflows to minimize network downtime and optimize 5G performance.
• Cross‑Functional Collaboration: Partner with network engineering, data science, and product teams to translate complex network pain points into scalable, production‑grade AI solutions.
• MLOps & Governance: Establish end‑to‑end MLOps/LLMOps practices, including real‑time model monitoring, fine‑tuning, security guardrails, and automated CI/CD deployment pipelines.

Requirements

• Bachelor’s degree or four or more years of relevant work experience.
• Eight or more years of experience in AI/ML engineering, software architecture, and real‑time data analytics.
• Hands‑on experience with generative AI concepts, including LLMs, prompt engineering, RAG, and agentic multi‑agent orchestration frameworks.
• Proven ability to build, deploy, and scale data analytics and AI solutions across cloud environments, specifically AWS and GCP.
• Strong background in device‑side processing, low‑latency edge deployment, or resource‑constrained model optimization.
• Production‑grade coding skills with Python, SQL, Kafka, Spark, and microservice architectures for real‑time streaming telemetry.

Preferred Qualifications

• Master’s degree or PhD in Computer Science, Data Science, or a related technical field.
• Experience with cloud AI ecosystems and frameworks (e.g., AWS Bedrock, Google Vertex AI, BigQuery, LangChain).
• Understanding of 5G infrastructure, network (4G/5G) protocols, telemetry counters, and operational performance metrics.
• Deep domain expertise in telecommunications (5G RAN, Core, Transport, 5G signaling).
• Experience implementing MLOps/LLMOps pipelines, security guardrails, and model evaluation standards for autonomous systems.

Schedule

This hybrid role includes a defined work location with a minimum of three days per week in the office (set by your manager) and the remainder working from home. Scheduled weekly hours are 40.

Benefits

• Medical, dental, and vision coverage.
• Short‑ and long‑term disability, basic and 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 and up to 6 personal days per year.
• Paid parental leave, adoption assistance, and tuition assistance.
• Vacation accrual starting at up to 15 days per year for new hires, increasing with service.
• Potential premium pay such as overtime, shift differential, holiday pay, and allowances.

Pay

The annual salary range for this full‑time position is $137,000.00 – $263,000.00, varying by location, skills, and experience. This is an incentive‑based role with the potential to earn additional compensation through premium pay and performance incentives. Part‑time roles are compensated proportionally to hours worked.