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.
Principal Machine Learning Engineer
Hybrid, Remote, US
Live, first seen by us 52 days ago- Pay
$140,000–185,000 · Total compensationPay period needs review — pay source
Job Specifications: Starting Wage: $140,000 - $185,000 + Annual Bonus Employment Type: Year Round
Experience with AI engineer to use, build, and monitor agentic solutions The expected Total Compensation for this role is $140,000 - $185,000 + Annual Bonus. Individual compensation decisions are based on a variety of factors. Job Benefits
Read the full posting- Work setting
Hybrid — work setting source
Listed location: Hybrid, Remote, US
Read the full posting- Employment
- Not stated
What you’ll work on
Full postingTurn data science models into reliable, monitored, maintainable production systems
Design ML platform patterns in Databricks for reliability, governance, and cost
Build trustworthy, scalable data foundations for training, inference, and monitoring
Provide technical leadership, mentoring, and design and code reviews
From the employer’s posting
Productionize ML models developed by data science into reliable, monitored, maintainable systems.
Architect ML platform patterns in Databricks that bring reliability, consistency, governance, performance, and cost discipline to ML and data workflows.
Build model data foundations that ensure training, inference, monitoring, and analytics data are trustworthy and scalable.
Provide technical leadership and mentoring across engineering, architecture, and development including design and code reviews.
What you’ll bring
All qualificationsCore experience
- Python and SQL Proficiency: strong in Python and SQL for building data pipelines, automation, model integrations, analytical workflows, and production services.
- Ownership: take responsibility to proactively advance projects, contribute to the organization, and develop the best solutions.
- Data Modeling and Pipeline Design: understand how to design reliable, well-structured data assets, including curated tables, feature datasets, batch pipelines, orchestration, data quality checks, and lineage.
- Communication: explain technical concepts, risks, tradeoffs, and recommendations clearly to technical and non-technical audiences.
Preferred experience
- Experience with dbt (Core) for modular data modeling, including testing, documentation, and dependency management
- Experience with AI engineer to use, build, and monitor agentic solutions
Qualification wording
Python and SQL Proficiency: strong in Python and SQL for building data pipelines, automation, model integrations, analytical workflows, and production services.
Ownership: take responsibility to proactively advance projects, contribute to the organization, and develop the best solutions.
Data Modeling and Pipeline Design: understand how to design reliable, well-structured data assets, including curated tables, feature datasets, batch pipelines, orchestration, data quality checks, and lineage.
Communication: explain technical concepts, risks, tradeoffs, and recommendations clearly to technical and non-technical audiences.
Experience with dbt (Core) for modular data modeling, including testing, documentation, and dependency management
Experience with AI engineer to use, build, and monitor agentic solutions
Education & alternatives
Preferred qualifications: - A graduate degree (Masters or PhD) in a quantitative field - Experience with dbt (Core) for modular data modeling, including testing, documentation, and dependency management
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Sep 13, 202652 days ago
- Recorded sightings
- 366
- Last seen by us
- Nov 5, 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
Time since we first saw it
Day 52
Similar jobs usually come down between day 6 and day 70.
At Vail Resorts, jobs usually come down by about day 33.
From 4,459 similar postings that came down, and 14 of Vail Resorts’s. Coming down is not always a hire.
Vail Resorts is hiring
1 open job
Open jobs by the week we first saw them, last 12 weeks.
- Takes jobs down quickly
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
- SQL
- Databricks
- dbt
- Delta Lake
- MLflow
- Spark
Where the posting names them
- Software Engineering Fundamentals: write clean, modular, testable, maintainable code and understand how to structure production-grade systems rather than one-off notebooks or scripts. - Python and SQL Proficiency: strong in Python and SQL for building data pipelines, automation, model integrations, analytical workflows, and production services. - Data Modeling and Pipeline Design: understand how to design reliable, well-structured data assets, including curated tables, feature datasets, batch pipelines, orchestration, data quality checks, and lineage.
- Build model data foundations that ensure training, inference, monitoring, and analytics data are trustworthy and scalable. - Architect ML platform patterns in Databricks that bring reliability, consistency, governance, performance, and cost discipline to ML and data workflows. - Identify and scope opportunities for ML engineering across the business for high-impact.
- Cloud and Platform Engineering: You are comfortable working in cloud-based data and ML environments and understand the foundations of permissions, environments, jobs, services, storage, networking, and cost-aware architecture. - Databricks Expertise: You’re familiar and experienced with the core parts of Spark, Unity Catalog, Delta Lake, Databricks Workflows, MLflow, model registry patterns, job/cluster optimization, and governance. - DevOps Practices: You use modern engineering practices such as Git, CI/CD, automated testing, code review, dependency management, environment management, and observability.
- A graduate degree (Masters or PhD) in a quantitative field - Experience with dbt (Core) for modular data modeling, including testing, documentation, and dependency management - Experience with AI engineer to use, build, and monitor agentic solutions
Your next step
Complete your application on jobs.vailresortscareers.com. The employer’s form will show what is required.
Applying through SAP SuccessFactors
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Already applied? Track this application
Demand for ML Engineer roles
New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
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
Our mission is to create the Experience of a Lifetime for our employees, so they can, in turn, create the Experience of a Lifetime for our guests. We own and operate the most renowned destination resorts in the world as well as regional and local ski areas outside major cities, and connect them all through one unrivaled network. We are looking for ambitious leaders, innovators and creators to join our talented team. If you’re ready to pursue your fullest potential, we want to get to know you!
Candidates for year-round positions are reviewed on a rolling basis. Applications will be accepted up to 90 days after the posting date, or until the position is filled (whichever is first).
Job Summary:
We are looking for a curious, driven, innovative machine learning engineer who takes initiative to solve problems and create environments that accelerate the development, deployment, and usage of data science models and AI to drive greater organizational impact.
The Data Science & Data Engineering team within the Enterprise Analytics organization builds data assets, predictive models, analytical applications, and platforms across the organization. Our team collaborates with business stakeholders, analysts, and technology teams to tackle high-impact use cases with state-of-the-art models and tools to grow the business, streamline costs, and improve guest experiences.
Job Specifications:
-
Starting Wage: $140,000 - $185,000 + Annual Bonus
-
Employment Type: Year Round
-
Shift Type: Full Time hours
-
Minimum Age: At least 18 years of age
-
Housing Availability: No
Job Responsibilities:
- Productionize ML models developed by data science into reliable, monitored, maintainable systems.
- Build model data foundations that ensure training, inference, monitoring, and analytics data are trustworthy and scalable.
- Architect ML platform patterns in Databricks that bring reliability, consistency, governance, performance, and cost discipline to ML and data workflows.
- Identify and scope opportunities for ML engineering across the business for high-impact.
- Develop reusable tools, libraries, standards, documentation, and production-readiness practices to enable data science and data engineering teams.
- Develop analytical and model-powered applications that turn data and ML outputs into usable business workflows for end users.
- Prepare the platform for future AI engineering, including LLM and agent-based systems, as the organization matures.
- Provide technical leadership and mentoring across engineering, architecture, and development including design and code reviews.
Job Requirements:
Technical Skills:
- Quantitative Foundation: B.S. degree in a quantitative field (e.g., Computer Science, Mathematics, Statistics, Economics, Operations Research, Engineering).
- Software Engineering Fundamentals: write clean, modular, testable, maintainable code and understand how to structure production-grade systems rather than one-off notebooks or scripts.
- Python and SQL Proficiency: strong in Python and SQL for building data pipelines, automation, model integrations, analytical workflows, and production services.
- Data Modeling and Pipeline Design: understand how to design reliable, well-structured data assets, including curated tables, feature datasets, batch pipelines, orchestration, data quality checks, and lineage.
- ML Lifecycle Fluency: understand the full model lifecycle: data collection, exploration, model development, validation, deployment, monitoring, retraining, and retirement.
- Production ML Patterns: understand core MLOps patterns such as model registries, feature/data versioning, reproducible environments, testing/validation, monitoring, and rollback.
- Cloud and Platform Engineering: You are comfortable working in cloud-based data and ML environments and understand the foundations of permissions, environments, jobs, services, storage, networking, and cost-aware architecture.
- Databricks Expertise: You’re familiar and experienced with the core parts of Spark, Unity Catalog, Delta Lake, Databricks Workflows, MLflow, model registry patterns, job/cluster optimization, and governance.
- DevOps Practices: You use modern engineering practices such as Git, CI/CD, automated testing, code review, dependency management, environment management, and observability.
- Application Development: You can build applications, APIs, dashboards, or workflow tools that sit on top of data and model outputs.
- System Design: You can reason through tradeoffs across reliability, latency, scale, cost, governance, maintainability, and ease of use.
Soft Skills:
- Curious: bring intellectual curiosity, an inquisitive nature, and a desire to deepen your knowledge and continue learning.
- Ownership: take responsibility to proactively advance projects, contribute to the organization, and develop the best solutions.
- Communication: explain technical concepts, risks, tradeoffs, and recommendations clearly to technical and non-technical audiences.
- Collaboration: work effectively cross-functionally with data scientists, data engineers, analysts, application engineers, product partners, and business stakeholders.
- Pragmatism: You know how to balance ideal architecture with business urgency, team maturity, operational constraints, and the need to ship.
Preferred qualifications:
- A graduate degree (Masters or PhD) in a quantitative field
- Experience with dbt (Core) for modular data modeling, including testing, documentation, and dependency management
- Experience with AI engineer to use, build, and monitor agentic solutions
The expected Total Compensation for this role is $140,000 - $185,000 + Annual Bonus. Individual compensation decisions are based on a variety of factors.
Job Benefits
- Ski/Mountain Perks! Free passes for employees, employee discounted lift tickets for friends and family AND free ski lessons
- MORE employee discounts on lodging, food, gear, and mountain shuttles
- 401(k) Retirement Plan
- Employee Assistance Program
- Excellent training and professional development
Full Time roles are eligible for the above, plus:
- Health Insurance; Medical Insurance, Dental Insurance, and Vision Insurance plans (for eligible seasonal employees after working 500 hours)
- Free ski passes for dependents
- Critical Illness and Accident plans
Employees can work remotely from British Columbia, Washington D.C., and the 16 U.S. states* in which we currently operate. This includes: California, Colorado, Indiana, Michigan, Minnesota, Missouri, New Hampshire, New York, Nevada, Ohio, Pennsylvania, Utah, Vermont, Washington State, Wisconsin, and Wyoming.
Please note that the ability to work in person or off-site, and the particulars related to such work, are subject to change at any time; and, accordingly, the Company reserves the right to change its policies and/or require in-person/in-office work or off-site work at any time in its sole discretion.
In completing this application, and when submitting related documentation, applicants may redact information that identifies their age, date of birth, and/or dates of attendance at or graduation from an educational institution.
We follow all federal, state, and local laws including restrictions on child/minor labor. Minors hired into this position will not be asked or permitted to engage in any activities restricted to adult workers.
Vail Resorts is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability, protected veteran status or any other status protected by applicable law.
Requisition ID 517322
Reference Date: 09/05/2026
Job Code Function: Data Science
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Job Specifications: Starting Wage: $140,000 - $185,000 + Annual Bonus Employment Type: Year Round
More source context
Experience with AI engineer to use, build, and monitor agentic solutions The expected Total Compensation for this role is $140,000 - $185,000 + Annual Bonus. Individual compensation decisions are based on a variety of factors. Job Benefits
- Location & working pattern
Hybrid, Remote, US
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.