AI Commercial & ML Ops Engineer

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.

THE JOB:

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.

THE DAY-TO-DAY:

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

THE IDEAL CANDIDATE:

5+ years of prior relevant experience in machine learning or art