Remote AI MLOps Engineer: Deploy & Scale ML

bcbst; Chattanooga (TN); A distancia; USD 120.000 - 160.000; Jornada completa

Descripción de la vacante

BlueCross BlueShield of Tennessee is seeking an AI MLOps Engineer to build, deploy, and operate machine learning solutions at scale in a fully remote role. You will collaborate with data scientists and software engineers in a modern production environment, following established patterns to move prototypes to production.

The role emphasizes hands-on implementation, continuous learning, and mentorship from experienced MLOps professionals within a tax‑paying not‑for‑profit organization.

Formación

• Bachelor’s degree in computer science or equivalent work experience.
• 2 years - Experience in software engineering and analytics technology.
• Experience handling large datasets to build data pipelines.
• Experience writing SQL and using Data Visualization tools.
• Experience solving complex problems and independently developing solutions.

Responsabilidades

• Model Deployment: Deploy ML models into production environments.
• Model Monitoring: Monitor models for drift and accuracy.
• Automation: Automate ML pipeline steps like preprocessing and training.
• Collaboration: Work with data scientists, software engineers, and IT operations to integrate models into business processes.
• Version Control and Governance: Manage model versions and governance policies.
• Optimization: Improve performance and scalability of ML systems.
• Exploring cloud tools to support data science use cases.

Conocimientos

Python

Cloud platforms

CI/CD

ML lifecycle

Data engineering

APIs & dashboards

Collaboration

Educación

Bachelor’s degree in computer science or equivalent

Herramientas

Terraform

Kubernetes/OpenShift

Databricks

MLflow

SQL

Data Visualization tools

Descripción del empleo

BlueCross BlueShield of Tennessee is seeking an AI MLOps Engineer to build, deploy, and operate machine learning solutions at scale in a fully remote role. You will collaborate with data scientists and software engineers in a modern production environment, following established patterns to move prototypes to production.

The role emphasizes hands-on implementation, continuous learning, and mentorship from experienced MLOps professionals within a tax‑paying not‑for‑profit organization.