Engineer II - AI/ML Engineering

Verizon • Irving, TX

1d • $72,000 - $129,000 • Hybrid

About The Position

Transitioning our enterprise roadmap toward modern agentic AI solutions requires dedicated engineering capability to architect autonomous workflows while establishing enterprise-grade governance and safety guardrails. This role is critical to scaling these complex systems safely, controlling cloud compute costs, and accelerating team delivery velocity across our AI/ML initiatives. As an AI/ML Engineer (MTS II), you will play a key role in industrializing AI/ML solutions across Verizon. You will collaborate with Enterprise Architecture, Data Science, and Data Engineering teams to build, deploy, and govern scalable machine learning and Generative AI systems across real-time and batch environments.

Requirements

• Bachelor’s degree or one or more years of relevant work experience.
• One or more years of relevant work experience, demonstrated through one or a combination of work and/or military experience, or specialized training.
• Experience in Machine Learning Engineering, Data Engineering, or Software Architecture.
• Hands-on experience with ML Engineering techniques and tools, including real-time/batch processors and model measurement techniques.
• Hands-on experience with cloud platforms (Google Cloud Platform preferred, or AWS) and modern ML development lifecycles.

Nice To Haves

• Knowledge of end-to-end Model Development & Management Lifecycles (MLOps/LLMOps), including model inventory tracking, validation, and governance frameworks.
• Hands-on experience with containerized microservices (Docker, Kubernetes) and CI/CD automation tools (Jenkins, GitLab CI).
• Experience designing and implementing agentic workflows, autonomous tool-calling systems, and RAG architectures using vector databases
• Proficiency in high-concurrency Python programmingFastAPI, PySpark, SQL, Kafka/Pulsar, and Linux/Unix environments.
• Familiarity with enterprise model governance frameworks (bias assessments, Responsible AI standards).

Responsibilities

• Design End-to-End GenAI & ML Solutions: Architecting and implementing agentic workflows, multi-step Retrieval-Augmented Generation (RAG) systems, and semantic retrieval pipelines for enterprise applications (e.g., personalization, next-best-action, and customer churn models).
• Build Automated Evaluation & Governance Pipelines: Establishing programmatic "evals" to continuously measure model accuracy, latency, hallucination rates, and task performance before and after deployment.
• Production Observability & Monitoring: Implementing enterprise guardrails, tracing, and continuous observability to maintain system uptime, enforce security/privacy standards, and diagnose performance bottlenecks.
• Optimize Cloud & Model Performance: Implementing model routing, prompt/semantic caching, and cost-control strategies across cloud AI platforms (GCP Vertex AI, AWS Bedrock) and self-hosted models.

Benefits

• 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
• up to 6 personal days per year
• paid parental leave
• adoption assistance
• tuition assistance
• premium pay such as overtime, shift differential, holiday pay, allowances
• up to 15 days of vacation per year

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level