Senior MLOps Engineer

Our team members are the key to our company’s success, and their health and well-being, as well as that of their families, is very important to us.

We offer a comprehensive benefits package that allows our team members stay healthy, plan for their future and maintain a healthy work-life balance. Benefits may vary with employment status. To see our fill list of Team Member Benefits please visit our career site:

We are looking for a highly skilled MLOps Engineer to support the end-to-end machine learning lifecycle, from experimentation to production deployment. This role focuses on building scalable, reliable, and automated ML infrastructure, enabling data science teams to deliver production-ready models efficiently and confidently.

• Design, build, and maintain production-grade ML pipelines on Databricks
• Operationalize ML models, including deployment, monitoring, and lifecycle management
• Build and maintain CI/CD pipelines for ML workflows
• Develop and manage real-time and streaming data pipelines
• Collaborate closely with Data Scientists to product ionize models efficiently
• Implement model versioning, experiment tracking, and reproducibility
• Define and enforce ML best practices, governance, and quality standards
• Monitor model performance and data drift; implement automated retraining strategies
• Optimize performance, scalability, and cost of distributed workloads
• Contribute to platform design for low-latency inference and scalable serving

• Strong experience with Databricks (Workflows, MLflow, Delta Lake)
• Deep expertise in Apache Spark (batch and streaming)
• Advanced Python skills (production-quality code)
• Hands-on experience with streaming / real-time systems
• Proven experience designing and implementing CI/CD pipelines
• Strong understanding of the ML lifecycle (training → deployment → monitoring → retraining)
• Experience building scalable, distributed data and ML pipelines

• Experience with Snowflake
• Knowledge of Kubernete
• Experience with Docker
• Familiarity with Terraform or other Infrastructure as Code tools
• Experience with feature stores (e.g. Snowflake or Databricks Feature Store, etc.)
• Experience with event-driven architectures (Kafka)
• Experience with model serving frameworks and low-latency APIs
• Monitoring and observability tools (ELK or similar)
• Familiarity with A/B testing / experimentation frameworks
• Experience with LLM deployment and serving
• Knowledge of RBAC, security, and governance in data/ML platforms
• Experience in cloud environments (Azure preferred)

• Fully automated, reliable ML pipelines from experimentation to production
• High-quality, observable, and maintainable ML systems
• Strong alignment between data science, engineering, and platform teams
• Scalable infrastructure that supports both batch and real-time workloads

• Recommendation Systems (real-time / near real-time customer personalization)
• LLM-based Products, including Text-to-SQL systems
• Customer Personalization

Be Iconic represents the roots of our culture. The Seminole Tribe of Florida remains the only unconquered tribe in the United States of America. The Tribe established Seminole Gaming in 1979, when it opened the first high-stakes bingo hall in the United States. Building on its rich heritage of courageous and groundbreaking achievements, the Seminole Tribe of Florida acquired Hard Rock International in March 2007—the first transaction of its kind by a Native American tribe.

Today, Hard Rock International remains one of the most globally recognized companies in the world, with Hard Rock Hotel, Casino, Cafe and Rock Shop venues in over 74 countries. With the continued growth of Seminole Gaming and Hard Rock International, Seminole Hard Rock Support Services was created to support all of our brands and lines of business. With the largest global footprint in the hospitality industry for over 50 years, our number-one job is to bring fun and excitement to our team members and our guests!