Principal Machine Learning Engineer

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