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Distinguished Engineer - ML/AI Engineer

Pay
$137,000–263,000/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: $137,000.00 - $263,000.00.
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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
  • Lead design and development of agentic AI, LLM and machine learning solutions

  • Build and deploy propensity models for churn risk and lifecycle triggers

  • Consolidate overlapping propensity models into shared, unified models

  • Manage end-to-end model pipelines from feature engineering to monitoring

  • Mentor junior data scientists and own models' lifecycle in high-impact areas

From the employer’s posting
Leading the design, development, and optimization of agentic AI, LLM, and machine learning/deep learning solutions.
Building, training, and deploying our high-priority propensity models to predict customer behaviors, churn risk, and key lifecycle triggers.
Drive consolidation of overlapping propensity models into a shared customer state and unified models, reducing operational and development cost.
Operating independently to manage end-to-end model development pipelines, from advanced feature engineering to production deployment and monitoring.
providing technical guidance and mentorship to junior data scientists.
Apply at Verizon

Posting record

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Status in our records
Live
First seen by us
Oct 13, 202622 days ago
Recorded sightings
65
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 22

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

From 4,296 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.

  • Python
  • R
  • SQL
  • AWS
  • Azure
  • BigQuery
  • GCP
  • PyTorch
  • scikit-learn
Where the posting names them
- Strong expertise and experience in machine learning/deep learning algorithms, including transformer, transfer learning, NLP, expertise in using Pytorch and scikit-learn packages, as well as probability calibration and time-based validation. - Experience with Python, R, and SQL for advanced statistical modeling and large-scale data extraction. - Experience with cloud platforms (e.g., GCP, AWS, or Azure) and production MLOps tools for tracking and maintaining model workflows.
- Experience with Python, R, and SQL for advanced statistical modeling and large-scale data extraction. - Experience with cloud platforms (e.g., GCP, AWS, or Azure) and production MLOps tools for tracking and maintaining model workflows. Even better if you have one or more of the following:
- Knowledge of LLM agent architecture: Google ADK, LangChain/LangGraph, multi-agent orchestration, retrieval-augmented generation RAG , MCP, A2A protocols, ONNX-based embeddings, vector databases and semantic search. - Knowledge of cloud-scale data engineering: Big Query pipelines, GCP (Cloud Run, Vertex AI). 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.
- Experience designing and measuring A/B tests or uplift models for targeting. - Strong expertise and experience in machine learning/deep learning algorithms, including transformer, transfer learning, NLP, expertise in using Pytorch and scikit-learn packages, as well as probability calibration and time-based validation. - Experience with Python, R, and SQL for advanced statistical modeling and large-scale data extraction.

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 Dist Engr-AI Engineer within our team of propensity modelers, you will be responsible for the technical execution of Verizon's transition to a modern, agile pod model. You will work directly at the critical touchpoints of the customer lifecycle and high-impact trigger events, providing the advanced machine learning support needed to unlock deep microsegmentation and hyper-personalization. Your work will directly empower marketers, optimize customer journeys, and drive down churn across our most critical customer segments.


Responsibilities include: 


  • Leading the design, development, and optimization of agentic AI, LLM, and machine learning/deep learning solutions.
  • Building, training, and deploying our high-priority propensity models to predict customer behaviors, churn risk, and key lifecycle triggers.
  • Drive consolidation of overlapping propensity models into a shared customer state and unified models, reducing operational and development cost.
  • Operating independently to manage end-to-end model development pipelines, from advanced feature engineering to production deployment and monitoring.
  • Serve as a subject matter expert on agentic development, machine learning and predictive modeling, providing technical guidance and mentorship to junior data scientists.
  • Owning the lifecycle of models deployed in high-impact areas, ensuring continuous optimization, accuracy, and measurable business performance.
  • Presenting complex model insights, performance metrics, and strategic recommendations clearly to senior leadership and cross-functional business partners.

What we're looking for...


You are a data science professional who thrives on solving complex analytical problems with minimal guidance. You have a proven track record of managing high-priority machine learning projects, and you excel at collaborating directly with business partners to deliver data-driven customer experiences that impact the bottom line.


You will need to have:


  • Bachelor's degree or six or more years of work experience.
  • Eight or more years of relevant experience required, demonstrated through work experience and/or military experience.
  • Experience working on high-priority or high-visibility technical initiatives within a corporate setting.
  • Experience designing and measuring A/B tests or uplift models for targeting.
  • Strong expertise and experience in machine learning/deep learning algorithms, including transformer, transfer learning, NLP, expertise in using Pytorch and scikit-learn packages, as well as probability calibration and time-based validation.
  • Experience with Python, R, and SQL for advanced statistical modeling and large-scale data extraction.
  • Experience with cloud platforms (e.g., GCP, AWS, or Azure) and production MLOps tools for tracking and maintaining model workflows.

Even better if you have one or more of the following:


  • Knowledge of LLM agent architecture: Google ADK, LangChain/LangGraph, multi-agent orchestration, retrieval-augmented generation RAG , MCP, A2A protocols, ONNX-based embeddings, vector databases and semantic search.
  • Knowledge of cloud-scale data engineering: Big Query pipelines, GCP (Cloud Run, Vertex AI).

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: $137,000.00 - $263,000.00.

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: $137,000.00 - $263,000.00.
Location & working pattern

Alpharetta, Georgia

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
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