Machine Learning Operations Intern

IMH

. Develop AI and machine learning solutions as part of the Enterprise AI Center of Enablement .

Posted 11/12/2026internshipRemote • Utah • United StatesEntry Level💰 $22 - $32 per hourWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing AI and machine learning solutions, with a strong focus on CI/CD pipelines, Infrastructure as Code, and model performance monitoring. Proficient in Python, SQL, and tools like MLflow for effective deployment and lifecycle management.

Highest-signal resume keywords

AI And Machine Learning Solutions DevelopmentCI/CD Pipeline ManagementInfrastructure As Code (IaC) Using TerraformPython Programming And OptimizationModel Performance Monitoring

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonSQLSparkMatlabMachine Learning Modeling TechniquesCode OptimizationStatistical AnalysisAutomated TestingData Pipeline OptimizationMLOps

Soft Skills

Effective CommunicationInterpersonal SkillsCollaboration

Tools & Technologies

GitDevOpsMLflowUnified Enterprise Agentic Architecture (UEAA)ContainersAPIs

Industry Keywords

CI/CDInfrastructure As CodeData Drift MonitoringModel Lifecycle ManagementDeclarative Automation Bundles

Tech Stack

Tools & technologies

PythonSparkSQLTerraform

About the role

Key responsibilities & impact

Develop AI and machine learning solutions as part of the Enterprise AI Center of Enablement
Build and maintain CI/CD pipelines for machine learning models and AI applications using Git and DevOps best practices
Deploy and monitor machine learning models on the Unified Enterprise Agentic Architecture (UEAA)
Package models and dependencies for reproducible deployment using tools such as MLflow, containers, and APIs
Develop and maintain Infrastructure as Code, including Terraform and Declarative Automation Bundles, to provision and manage ML platform resources
Support model deployment and lifecycle management within UEAA
Implement monitoring for model performance, data drift, and system health
Troubleshoot production issues
Optimize SQL queries, Python code, and data pipelines for performance, reliability, and cost
Contribute to automated testing and validation of models and pipelines before release
Collaborate with data scientists, AI engineers, and MLOps engineers
Document processes, code, and deployment standards

Requirements

What you’ll need

Understanding of statistical and machine learning modeling techniques
Experience programming using Python, SQL, Spark, and Matlab
Effective verbal, written, and interpersonal communication skills
Enrolled in a higher education institution focused on mathematics, computer science, data science, or another quantitative and technical field (preferred)
Experience with Git, DevOps, and CI/CD (preferred)
Experience with MLOps platform development and Infrastructure as Code (IaC) (preferred)
Code optimization experience, including SQL query tuning and Python optimization (preferred)
Must reside or plan to reside outside California, Connecticut, Hawaii, Illinois, Maine, Massachusetts, Minnesota, New York, Pennsylvania, Rhode Island, Virginia, Vermont, and Washington
Availability Monday-Friday during regular business hours
Microsoft Teams video interview required; potential onsite interviews and meetings

Benefits

Comp & perks

Generous benefits package covering programs supporting wellness, health, security, connection, and engagement
Remote work options and flexible work options where approved and stated
Company equipment and remote-work support subject to Intermountain policies