AI MLOps Engineer

Location: Remote within the USA; final interviews onsite at the Chattanooga, Tennessee headquarters are required

Company

hirify.global is a not-for-profit health organization focused on supporting better health through production data and machine learning solutions.

What you will do

• Deploy machine learning models efficiently and reliably into production environments.
• Monitor model performance, detect model drift, and maintain model accuracy and effectiveness.
• Automate data preprocessing, model training, evaluation, and other machine learning pipeline stages.
• Collaborate with data scientists, software engineers, and IT operations to integrate models into business processes.
• Manage model version control, reproducibility, and governance compliance.
• Optimize the performance and scalability of ML systems and explore cloud tools supporting data science use cases.

Requirements

• Bachelor’s degree in computer science or equivalent work experience; equivalent experience is defined as four years in a corporate environment.
• At least two years of experience in software engineering and analytics technology, including academic experience.
• Proficiency in Python or similar programming languages, with experience in scripting, data processing, or machine learning workflows.
• Experience with cloud platforms, large datasets, data pipelines, SQL, and data visualization tools.
• Understanding of CI/CD, Git-based workflows, automated testing, builds, deployments, machine learning lifecycle management, and model versioning.
• Must be able to work remotely within the USA and attend final interviews onsite in Chattanooga, Tennessee.

Nice to have

• Familiarity with OpenShift, Kubernetes, and containerized applications.
• Experience with Terraform and infrastructure as code.
• Exposure to Databricks for data engineering, analytics, or machine learning workflows.

Culture & Benefits

• Fully remote work arrangement with required onsite final interviews.
• Hands-on individual contributor role with continuous learning and mentorship from experienced MLOps professionals.
• Opportunity to contribute to real-world production systems and modern MLOps practices.
• Employee position at a tax-paying not-for-profit organization.
• Visa sponsorship is available for this role.