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Principal Machine Learning Engineer

Vail Resorts Corporate United States

United States

Today

$140k - $185k/yr Full time Agent Based Systems Artificial Intelligence Big Data

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Job Description

Vail Resorts Corporate’s Enterprise Analytics team is seeking a Principal Machine Learning Engineer to productionize ML and help evolve the ML and AI engineering platform across the organization.

Responsibilities

Productionize machine learning models created by data science into reliable, monitored, and maintainable systems
Build scalable model data foundations covering training, inference, monitoring, and analytics data reliability
Architect machine learning platform patterns in Databricks to deliver reliability, consistency, governance, performance, and cost discipline
Identify and scope high-impact machine learning engineering opportunities across the business
Create reusable tools, libraries, standards, documentation, and production-readiness practices for data science and data engineering teams
Develop analytical and model-powered applications that convert data and ML outputs into end-user business workflows
Prepare the platform for future AI engineering as the organization matures, including LLM and agent-based systems
Provide technical leadership and mentoring across engineering, architecture, and development, including design and code reviews

Requirements

B.S. degree in a quantitative field, such as Computer Science, Mathematics, Statistics, Economics, Operations Research, or Engineering
Write clean, modular, testable, maintainable code and structure production-grade systems (not one-off notebooks or scripts)
Strong Python and SQL skills for data pipelines, automation, model integrations, analytical workflows, and production services
Knowledge of reliable, well-structured data assets including curated tables, feature datasets, batch pipelines, orchestration, data quality checks, and lineage
Understanding of the full model lifecycle: data collection, exploration, model development, validation, deployment, monitoring, retraining, and retirement
Familiarity with MLOps patterns including model registries, feature/data versioning, reproducible environments, testing/validation, monitoring, and rollback
Comfort working in cloud-based data and ML environments, including foundations of permissions, environments, jobs, services, storage, networking, and cost-aware architecture
Experience with core components such as Spark, Unity Catalog, Delta Lake, Databricks Workflows, and MLflow, including model registry patterns, job/cluster optimization, and governance
Use modern engineering practices: Git, CI/CD, automated testing, code review, dependency management, environment management, and observability
Ability to build applications, APIs, dashboards, or workflow tools on top of data and model outputs
Ability to reason through tradeoffs across reliability, latency, scale, cost, governance, maintainability, and ease of use
Curiosity and willingness to deepen knowledge through continued learning
Ownership to proactively advance projects and contribute best solutions
Clear communication of technical concepts, risks, tradeoffs, and recommendations to technical and non-technical audiences
Effective cross-functional collaboration with data scientists, data engineers, analysts, application engineers, product partners, and business stakeholders
Pragmatism to balance ideal architecture with business urgency, team maturity, operational constraints, and the need to ship

Preferred Qualifications

Graduate degree (Masters or PhD) in a quantitative field
Experience with dbt (Core) for modular data modeling, including testing, documentation, and dependency management
Experience as an AI engineer to use, build, and monitor agentic solutions

Technologies

Python
SQL
Databricks
Spark
Unity Catalog
Delta Lake
Databricks Workflows
MLflow
Git
CI/CD
LLM
Agent-based systems

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
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

Job Details

Location: United States (hybrid)
Salary: USD 140,000 - 185,000 per year
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
Requisition ID: 517322
Reference Date: 09/05/2026
Job Code Function: Data Science
Remote work: Employees can work remotely from British Columbia, Washington D.C., and the 16 U.S. states where the company currently operates: California, Colorado, Indiana, Michigan, Minnesota, Missouri, New Hampshire, New York, Nevada, Ohio, Pennsylvania, Utah, Vermont, Washington State, Wisconsin, Wyoming

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