AI Commercial, ML Ops Engineer

MGM Resorts International

Senior AI and ML Ops Engineer designing and optimizing deployment pipelines for machine learning solutions at MGM Resorts. Collaborating with Data Science and Engineering teams to produce impactful AI applications.

Posted 5/20/2026full-timeFlorida, Massachusetts, Missouri, Nevada, New Jersey, Texas • 🇺🇸 United StatesMid-LevelSenior💰 $130,100 - $173,500 per yearWebsite

Tech Stack

Tools & technologies

AirflowAWSAzureCloudDockerGoogle Cloud PlatformKubernetesPySparkPythonPyTorchScikit-LearnTensorflow

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

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 PySpark
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 TensorFlow, PyTorch, Scikit-learn, or similar machine learning frameworks preferred.

Benefits

Comp & perks

Prioritize your wellness, access programs crafted to nurture your mental and physical health.
Enjoy unbeatable discounts on hotel stays, dining, retail, entertainment, and exclusive partner perks for travel, tech, and beyond!
Savor delicious meals for free in our employee dining room.
Park with ease—whether you're on or off shift, it's free!
From healthcare to financial support and generous time-off options, we’ve got you covered.
Elevate your career with development programs, connect through networking events, and make a difference with community volunteer opportunities.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

machine learningartificial intelligencePythonPySparkCI/CDDockerKubernetesTensorFlowPyTorchScikit-learn

Soft Skills

technical leadershipmentoringinfluencingcollaborationproblem-solvingcommunicationstrategic thinkingadaptabilityanalytical thinkingproject management