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Senior AI/ML Engineer - AI Live Operations

Pay
$111,500–194,000/yearLocation-specific pay — pay source
The salary will vary depending on your location and confirmed job-related skills and experience. This is an incentive based position with the potential to earn more. For part-time roles, your compensation will be adjusted to reflect your hours. The annual salary range for the location(s) listed on this job requisition based on a full-time schedule is: $111,500.00 - $194,000.00.
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Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting
  • Build real-time monitoring of throughput, latency and LLM token costs

  • Monitor production models for data drift and accuracy loss

  • Deploy safety filters and guardrails against hallucinations and harmful content

  • Resolve production model incidents as senior escalation contact

  • Build CI/CD pipelines to retrain and release models without downtime

From the employer’s posting
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
Deploying real-time safety filters, system guardrails, and input/output moderators to mitigate model hallucinations and prevent inappropriate content generation
Resolving production model incidents as a senior escalation contact, diagnosing issues with live models, and shipping immediate hotfixes or prompt adjustments
Developing automated continuous integration and continuous deployment pipelines to retrain, validate, and seamlessly release updated models without downtime
Education & alternatives
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.
Apply at Verizon

Posting record

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Actively hiringFirst seen by us 4 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Oct 30, 20264 days ago
Recorded sightings
6
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$166K–$240K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 1,279 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 4

Early. Similar jobs usually come down between day 6 and day 69.

From 4,284 similar postings that came down. Coming down is not always a hire.

Verizon is hiring

16 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Takes jobs down quickly
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Java
  • Python
  • AWS
  • Azure
  • Kafka
  • MLflow
  • Spark
  • Airflow
  • C++
  • GCP
Where the posting names them
- 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.
- 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. If Verizon and this role sound like a fit for you, we encourage you to apply even if you don’t meet every even better qualification listed above.
- 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.

Your next step

Complete your application on verizon.wd12.myworkdayjobs.com. The employer’s form will show what is required.

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About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

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.


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.

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.

If Verizon and this role sound like a fit for you, we encourage you to apply even if you don’t meet every even better qualification listed above.


Where you’ll be working

In this hybrid role, you'll have a defined work location that includes working from home and a minimum of three days per week in the office, which will be set by your manager. Employees are responsible for maintaining compliance with hybrid work policies.

Scheduled Weekly Hours

40

Equal Employment Opportunity 

Verizon is an equal opportunity employer. We evaluate qualified applicants without regard to veteran status, disability or other legally protected characteristics.

Benefits and Compensation

Our benefits are designed to help you move forward in your career, and in areas of your life outside of Verizon. From health and wellness benefit options including: 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. We also offer a 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 and tuition assistance, plus other incentives, we’ve got you covered with our award-winning total rewards package. Depending on the role, employees have the opportunity to receive compensation in the form of premium pay such as overtime, shift differential, holiday pay, allowances, etc. Newly hired employees receive up to 15 days of vacation per year, which grows with additional service. For part-timers, your coverage will vary as you may be eligible for some of these benefits depending on your individual circumstances.

The salary will vary depending on your location and confirmed job-related skills and experience. This is an incentive based position with the potential to earn more. For part-time roles, your compensation will be adjusted to reflect your hours.

The annual salary range for the location(s) listed on this job requisition based on a full-time schedule is: $111,500.00 - $194,000.00.

Source details

View original posting ↗

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Pay
The salary will vary depending on your location and confirmed job-related skills and experience. This is an incentive based position with the potential to earn more. For part-time roles, your compensation will be adjusted to reflect your hours. The annual salary range for the location(s) listed on this job requisition based on a full-time schedule is: $111,500.00 - $194,000.00.
Location & working pattern

Basking Ridge, New Jersey

Where you’ll be working In this hybrid role, you'll have a defined work location that includes working from home and a minimum of three days per week in the office, which will be set by your manager. Employees are responsible for maintaining compliance with hybrid work policies. Scheduled Weekly Hours
Work authorization

No clear work-authorization passage found. Eligibility is unconfirmed.

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