Experience using Python for scripting, data processing, or supporting machine learning workflows
Experience working with a cloud-based platform (e.g., AWS, Azure, or GCP) to develop, deploy, or support data or machine learning solutions
Exposure to CI/CD practices, including Git-based workflows, automated testing, builds, and deployments
Understanding of the machine learning lifecycle, including experimentation, model versioning, and reproducibility (e.g., MLflow or similar tools)
Foundational knowledge of data engineering concepts, such as data ingestion, transformation, validation, and storage
Experience contributing to simple full-stack applications, including:
Python-based backend APIs
Basic front-end views or dashboards to display data or model outputs
Willingness to follow established patterns and best practices to help move ML solutions from prototype to production
Familiarity with OpenShift or Kubernetes, and working with containerized applications
Experience building or maintaining infrastructure-as-code using Terraform (e.g., defining resources and managing environments)
Exposure to Databricks for data engineering, analytics, or machine learning workflows
Why Join Us?
Note
Final interviews onsite at our Chattanooga, TN headquarters are required for this role.
Sponsorship is not available for this role.
Job Duties & 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 Responsibility
Exploring cloud tools and technologies that assist data science with implementing their usecases.
Job Qualifications
Education
Bachelor's degree in computer science or equivalent work experience required. Equivalent experience is defined as 4 years of professional work experience in a corporate environment.
Experiences
2 years - Experience in software engineering and analytics technology (academic experience included)
Experience handling large datasets to build data pipelines.
Experience writing SQL and using Data Visualization tools.
Experience solving complex problems and independently developing solutions.
Skills/Certifications
Programming: Demonstrated proficiency in languages like Python or similar languages
Data Engineering: Strong understanding of data processing and storage solutions.
Problem-Solving: Ability to troubleshoot issues in ML models and infrastructure.
Ability to work independently with minimal supervision or function in a team environment sharing responsibility, roles, and accountability.
Excellent oral and written communication skills
Strong interpersonal and organizational skills
Number of Openings Available
1
Worker Type:
Employee
Company:
BCBST BlueCross BlueShield of Tennessee, Inc.
Applying for this job indicates your acknowledgement and understanding of the following statements:
Further information regarding BCBST's EEO Policies/Notices may be found by reviewing the following page:
BCBST's EEO Policies/Notices
BlueCross BlueShield of Tennessee is not accepting unsolicited assistance from search firms for this employment opportunity. All resumes submitted by search firms to any employee at BlueCross BlueShield of
Benefits
Health insuranceVision insuranceRemote work options
Additional Information
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.
Bcbst · TN, Chattanooga, Remote