AI Commercial & ML Ops Engineer

US, Nevada

The SHOW comes alive at MGM Resorts International

Have you ever wondered what it would be like to work in a place full of excitement, diversity, and entertainment? Are you enthusiastic about being a team player in one of the most fascinating industries in the world? At MGM Resorts, we seek individuals like YOU to create unique and show-stopping experiences for our guests.

We are seeking a senior-level Artificial Intelligence and Machine Learning Operations Engineer to design, implement, and optimize scalable machine learning and artificial intelligence deployment pipelines that power real-world business impact.

In this role, you will partner closely with Data Science, Data Engineering, and Analytics teams to ensure models are production-ready, performant, secure, and scalable across cloud platforms. You will automate and operationalize the full machine learning lifecycle, from data ingestion through retraining, while establishing best practices, governance frameworks, and enterprise standards for Artificial Intelligence and Machine Learning Operations.

This is a highly visible individual contributor role that combines hands‑on engineering with strategic influence across various initiatives.

• Design, build, and operate end‑to‑end machine learning and artificial intelligence pipelines supporting batch, streaming, and real‑time inference use cases
• Automate the full machine learning lifecycle including ingestion, feature engineering, training, validation, deployment, monitoring, and retraining
• Implement CI/CD pipelines for machine learning systems with automated testing, validation gates, and controlled model promotion
• Develop orchestration workflows using tools such as Airflow, Kubeflow, and MLflow for experiment tracking and governance
• Optimize artificial intelligence workloads for performance, scalability, and cost efficiency using distributed compute and cloud‑native services
• Establish monitoring and observability frameworks including performance metrics, data quality checks, drift detection, and bias monitoring
• Design automated retraining strategies including trigger‑based, schedule‑based, and performance‑based refresh cycles
• Create repeatable prompting frameworks and artificial intelligence guardrails to support safe and effective AI‑assisted development
• Implement access controls, secrets management, compliance standards, and security best practices across machine learning and artificial intelligence platforms
• Evaluate and operationalize emerging artificial intelligence technologies and vendor tools, identifying measurable business value
• Mentor engineers and data scientists on Machine Learning Operations best practices and influence enterprise‑wide architectural standards

• 5+ years of prior relevant experience in machine learning or artificial intelligence engineering, Data Science, or Analytics Engineering
• Bachelor’s degree in Computer Science, Data Engineering, or related field required
• Deep experience with machine learning and artificial intelligence pipeline development and full lifecycle automation
• Demonstrated ability to provide technical leadership in Machine Learning Operations strategies and pipeline standardization
• Proven impact on improving reliability, scalability, and efficiency of machine learning and artificial intelligence solutions
• Strong proficiency in Python and Py Spark
• Experience designing and implementing CI/CD for machine learning workflows, including version control systems such as Git and DVC
• Experience with monitoring, logging, drift detection, and automated retraining frameworks
• Experience with cloud platforms such as Databricks, AWS, GCP, or Azure
• Proficiency in containerization and orchestration including Docker and Kubernetes
• Experience with orchestration and lifecycle management tools such as Airflow, Kubeflow, MLflow, or similar platforms
• Experience guiding teams on artificial intelligence automation best practices
• Experience supporting marketing, revenue, or operations analytics teams preferred
• Familiarity with Tensor Flow, PyTorch, Scikit‑learn, or similar machine learning frameworks preferred

• Prioritize your…