Principal Machine Learning Engineer

Lead machine learning engineering across production systems, data foundations, and the Databricks platform for Vail Resorts Corporate.

Responsibilities

• Productionize ML models from data science teams into reliable, monitored, maintainable systems.
• Build model data foundations that support trustworthy and scalable training, inference, monitoring, and analytics data.
• Architect ML platform patterns in Databricks to improve reliability, consistency, governance, performance, and cost discipline.
• Spot and scope high-impact ML 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 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.

Requirements

• B.S. degree in a quantitative field (examples: Computer Science, Mathematics, Statistics, Economics, Operations Research, Engineering).
• Ability to 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.
• Understanding of reliable, well-structured data assets such as curated tables, feature datasets, batch pipelines, orchestration, data quality checks, and lineage.
• Knowledge of the full model lifecycle: data collection, exploration, model development, validation, deployment, monitoring, retraining, and retirement.
• Familiarity with core 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 Databricks components: 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, observability.
• Build applications on top of data and model outputs, including APIs, dashboards, or workflow tools.
• Ability to reason through tradeoffs across reliability, latency, scale, cost, governance, maintainability, and ease of use.
• Curiosity and eagerness to deepen knowledge through continued learning.
• Ownership mindset to proactively advance projects and contribute best solutions.
• Clear communication of technical concepts, risks, tradeoffs, and recommendations to technical and non-technical audiences.
• 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 building and monitoring agentic solutions for AI engineering use cases.

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 options: Medical, Dental, and Vision plans (for eligible seasonal employees after working 500 hours).
• Free ski passes for dependents.
• Critical Illness and Accident plans.

Job Details

• Salary: USD 140,000 - 185,000 per year
• Starting wage: $140,000 - $185,000 + annual bonus
• Location: United States (hybrid)
• Employment type: Year round
• Shift type: Full time hours
• Minimum age: At least 18 years of age
• Housing availability: No
• Remote work availability: employees can work remotely from British Columbia, Washington D.C., and the 16 U.S. states currently operating in: California, Colorado, Indiana, Michigan, Minnesota, Missouri, New Hampshire, New York, Nevada, Ohio, Pennsylvania, Utah, Vermont, Washington State, Wisconsin, Wyoming.
• Requisition ID: 517322
• Reference date: 09/05/2026
• Job code function: Data Science