Senior AI/ML Engineer - AI Live Operations

Verizon • Basking Ridge, NJ

8d • Hybrid

About The Position

As a Senior AI/ML Engineer on Verizon’s AI Live Operations team, you will apply expertise in data science, system orchestration, and software engineering to maintain the stability, safety, and efficiency of deployed AI models. You will be an individual contributor responsible for machine learning system health as models encounter real-world data and production traffic. Verizon is industrializing its data science and AI capabilities, scaling production AI systems across telecommunications and moving from millions of automated predictions to trillions of real-time inferences.

The role focuses on production monitoring and observability, ongoing model evaluation, safety controls, resilient fallback mechanisms, automated model deployment, and incident response. You will collaborate with platform architects, data science teams, and peer engineering groups to scale backend systems across cloud, on-premises, and edge infrastructures, while supporting technical alignment and secure, ethical AI practices.

This is a hybrid role with a defined work location combining work from home and at least three days per week in the office. The manager determines the work location, and employees must comply with hybrid work policies. Scheduled weekly hours are 40.

Requirements

• Bachelor’s degree or four or more years of work experience.
• Four or more years of relevant experience, demonstrated through work and/or military experience or specialized training.
• Expertise at the intersection of data science, software development, and operations.
• Ability to address real-time challenges arising when machine learning systems are used by real-world users.
• Precision, attention to system resilience, and ability to produce clean, scalable code.

Nice To Haves

• Master’s degree in computer science, data science, electrical engineering, mathematics, or another highly technical discipline.
• Hands-on experience deploying, monitoring, and debugging complex machine learning or deep learning models in large-scale production environments.
• Practical familiarity with MLOps frameworks and automated pipeline tools, including Airflow, Kubeflow, or MLflow.
• Advanced programming expertise in Python, Java, or C++, with a strong grasp of data structures and cloud systems such as AWS, Google Cloud, or Azure.
• Experience developing safety guardrail middleware, system monitoring dashboards, and telemetry systems for Generative AI applications.
• Knowledge of distributed compute architectures, database design, and real-time streaming technologies such as Kafka or Spark.

Responsibilities

• Build and maintain real-time monitoring and observability pipelines for system throughput, latency, and large language model token consumption costs.
• Monitor production model behavior to detect data drift and model degradation and maintain predictive accuracy.
• Implement automated continuous evaluation loops using user feedback and ground-truth telemetry to assess performance.
• Deploy real-time safety filters, system guardrails, and input/output moderators to mitigate hallucinations and inappropriate content.
• Develop fallback systems that route failures to traditional rule-based software or human queues to preserve end-user experience.
• Develop automated continuous integration and continuous deployment pipelines to retrain, validate, and release updated models without downtime.
• Resolve production model incidents as a senior escalation contact by diagnosing live model issues and delivering hotfixes or prompt adjustments.
• Collaborate with platform architects and core data science teams to scale backend architectures across cloud, on-premises, and edge network infrastructures.
• Partner with engineering and development teams to align technically, conduct code reviews, and promote secure and ethical AI standards.
• Mentor junior team members and share technical knowledge across the engineering community.

Benefits

• Medical, dental, and vision insurance.
• Short- and long-term disability insurance.
• Basic and supplemental life insurance and AD&D insurance.
• Identity theft protection, pet insurance, and group home and 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.
• Tuition assistance.
• Other incentives and an award-winning total rewards package.
• Potential premium pay, such as overtime, shift differential, holiday pay, and allowances, depending on the role.
• Up to 15 days of vacation per year for newly hired employees, with additional vacation as service grows.

What This Job Offers

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