We are looking for an Associate MLOps Engineer to support data science teams in building, deploying, and operating machine learning solutions at scale. This is a hands-on, individual contributor role focused on technical execution, continuous learning, and collaboration. You will work closely with data scientists and engineers in a modern production environment.
Key Highlights
Model Deployment
Model Monitoring
Automation
Collaboration
Version Control and Governance
Optimization
Key Responsibilities
Model Deployment: Ensuring that machine learning models are deployed efficiently and reliably into production environments.
Model Monitoring: Continuously monitoring the performance of models to detect issues like model drift and ensure they remain accurate and effective.
Automation: Automating the machine learning pipeline, including tasks like data preprocessing, model training, and evaluation.
Collaboration: Working closely with data scientists, software engineers, and IT operations to integrate machine learning models into business processes.
Version Control and Governance: Managing version control for models and ensuring compliance with governance policies.
Optimization: Identifying and implementing ways to improve the performance and scalability of ML systems
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Technical Skills Required
Python
AWS
Azure
GCP
CI/CD practices
Git-based workflows
Automated testing
Builds
Deployments
MLflow
Data engineering concepts
Data ingestion
Transformation
Validation
Storage
Databricks
Benefits & Perks
Fully-remote role
Tax-paying not-for-profit organization
Opportunity to contribute to real-world production systems
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Nice to Have
OpenShift or Kubernetes
Terraform
Databricks
Job Description
BlueCross BlueShield of Tennessee is looking for an Associate MLOps Engineer to support data science teams in building, deploying, and operating machine learning solutions at scale. This is a hands-on, individual contributor role focused on technical execution, continuous learning, and collaboration. You will work closely with data scientists and engineers in a modern production environment, with mentorship from experienced MLOps professionals.
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