Senior AI/ML Live Operations Engineer

Cellco Partnership; Basking Ridge (NJ); Hybrid; USD 140,000 - 190,000; Full time

Job summary

Cellco Partnership seeks a Senior AI/ML Engineer - AI Live Operations to ensure stability, safety, and efficiency of deployed AI models in production. You will build real-time monitoring pipelines, address data drift, run automated evaluation loops, and deploy safety filters while collaborating with platform architects and data science teams.

This hybrid role involves working from home with defined location and opportunities to scale backend architectures across cloud and on‑prem environments.

Qualifications

• Bachelor's degree or four or more years of work experience.
• Four+ years of relevant experience in ML/AI or related fields.
• Master's degree in a technical field is a plus.

Responsibilities

• Build real-time monitoring and observability pipelines for model throughput and latency.
• Monitor production models for data drift and degradation to maintain accuracy.
• Implement automated evaluation loops using user feedback and telemetry.
• Deploy real-time safety filters and moderators to prevent inappropriate content.
• Integrate robust fallbacks to route failures to rule-based systems or human queues.
• Develop CI/CD pipelines to retrain, validate, and release updated models without downtime.
• Resolve production incidents as senior escalation contact and ship hotfixes.
• Collaborate with platform and data science teams to scale architectures across cloud/on‑prem.
• Partner with peers to ensure code quality, alignment, and ethical AI practices.

Skills

Python

Java

C++

Cloud platforms

Education

Bachelor's degree or four or more years of work experience

Master's degree in a technical field

Tools

Airflow

Kubeflow

MLflow

Job description

Cellco Partnership seeks a Senior AI/ML Engineer - AI Live Operations to ensure stability, safety, and efficiency of deployed AI models in production. You will build real-time monitoring pipelines, address data drift, run automated evaluation loops, and deploy safety filters while collaborating with platform architects and data science teams.

This hybrid role involves working from home with defined location and opportunities to scale backend architectures across cloud and on‑prem environments.