Senior AI Engineer - Live Operations
About The Position
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. At Verizon, we are on a multi-year journey to industrialize our data science and AI capabilities. Very simply, this means that AI will fuel decisions and business processes across the company. At over one hundred thirty billion dollars in annual revenue, this is a pioneering opportunity to build and scale production AI systems in the telecommunications industry. With our leadership in bringing 5G network nationwide, you will help us transition from millions of automated predictions to trillions of real-time inferences.
Requirements
- Bachelor's degree or four or more years of work experience.
- Four or more years of relevant experience required, demonstrated through work experience and/or military experience.
Nice To Haves
- 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.
Responsibilities
- 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.
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
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What This Job Offers
Job Type
Full-time
Career Level
Senior
