Senior AI/ML Engineer - AI Live Operations

Cellco Partnership

Basking Ridge (NJ)

Hybrid

USD 140,000 - 190,000

Full time

5 days ago
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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

When you join Verizon

You want more out of a career. A place to share your ideas freely - even if they're daring or different. Where the true you can learn, grow, and thrive. At Verizon, we power and empower how people live, work and play by connecting them to what brings them joy. We do what we love - driving innovation, creativity, and impact in the world. Our V Team is a community of people who anticipate, lead, and believe that listening is where learning begins. In crisis and in celebration, we come together - lifting our communities and building trust in how we show up, everywhere & always. Want in? Join the #VTeamLife.

What you'll be doing...

As a Senior AI/ML Engineer - AI Live Operations, you will apply your advanced technical expertise in data science, system orchestration, and software engineering to maintain the stability, safety, and efficiency of our deployed artificial intelligence models. You will be a key individual contributor within the Live Operations team, taking responsibility for the health of machine learning systems once they are exposed to real-world datasets and production traffic.

In this role, your responsibilities will include:
  • Building and maintaining real-time monitoring and observability pipelines to track system throughput, latency, and token consumption costs for large language models.
  • Monitoring production model behavior to identify data drift and model degradation, ensuring our systems maintain high predictive accuracy over time.
  • Implementing automated continuous evaluation loops that capture user feedback and ground-truth telemetry to dynamically assess performance.
  • Deploying real-time safety filters, system guardrails, and input/output moderators to mitigate model hallucinations and prevent inappropriate content generation.
  • Integrating robust fallback systems, including routing failures to traditional rule-based software systems or human queues, to preserve end-user experience.
  • Developing automated continuous integration and continuous deployment pipelines to retrain, validate, and seamlessly release updated models without downtime.
  • Resolving production model incidents as a senior escalation contact, diagnosing issues with live models, and shipping immediate hotfixes or prompt adjustments.
  • Collaborating with platform architects and core data science teams to scale backend architectures across cloud, on-premises, and edge network infrastructures.
  • Partnering with peer engineering and development teams to foster technical alignment, conduct code reviews, and champion secure, ethical AI standards.
What we’re looking for...

You are a highly skilled engineer who excels in the intersection of data science, software development, and operations. You understand that machine learning models are not static, and you thrive on solving the complex, real-time challenges that occur once algorithms meet actual users. You are a self-starter who values precision, system resilience, and clean, scalable code. You enjoy mentoring junior team members and sharing technical knowledge across the larger engineering community.

You’ll need to have:
  • Bachelor's degree or four or more years of work experience.
  • Four or more years of relevant experience required, demonstrated through one or a combination of work and/or military experience, or specialized training.
Even better if you have one or more of the following:
  • Master's degree in computer science, data science, electrical engineering, mathematics, or another highly technical discipline.
  • Extensive 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.
  • Deep 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.
Where you'll be working

In this hybrid role, you'll have a defined work location that includes working from home and a mi

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