MLOps Engineer - Healthcare (Remote)

Experian

2d • Remote

About The Position

Reporting to the Director of Analytics, the MLOps Engineer will join our team in building and scaling machine learning solutions that address critical challenges in the healthcare revenue cycle.
You will collaborate with data scientists, software engineers, and product teams to bring ML products from prototype to production, with an emphasis on automation, monitoring, and continuous improvement.

Requirements

• 3+ years of experience in MLOps, DevOps, or ML engineering roles.
• 3+ years experience with AWS services for ML (e.g., SageMaker, Lambda, Step Functions, S3, ECR, CloudWatch).
• 3+ years Experience with ML lifecycle tools such as MLflow, TensorFlow Serving, or Kubeflow.
• Proficiency with containerization and orchestration tools (Docker, Kubernetes/EKS).
• Experience with CI/CD pipelines, infrastructure as code (e.g., Terraform, CloudFormation), and monitoring/logging tools.
• Experience working in collaborative, cross-functional teams
• Bachelor's degree in Computer Science, Engineering, Data Science, or a related field.

Nice To Haves

• Experience in the healthcare domain, especially with claims or EHR data, and familiarity with standards like ICD and CPT.
• Exposure to NLP, Bayesian modeling, or real-time ML systems.
• Familiarity with Agile development methodologies.
• AWS certifications (e.g., Machine Learning Specialty, DevOps Engineer).

Responsibilities

• Design, build, and maintain scalable MLOps pipelines for model training, validation, deployment, and monitoring using AWS services.
• Implement infrastructure as code and CI/CD workflows to support rapid experimentation and reliable production releases.
• Collaborate with data scientists to productionize ML models and ensure reproducibility, versioning, and traceability.
• Monitor model performance and data drift in production environments, and implement automated retraining and alerting mechanisms.
• Optimize ML workflows using tools such as SageMaker, Airflow, Docker, Kubernetes (EKS), and Step Functions.
• Ensure compliance with healthcare data standards and security best practices (e.g., HIPAA).
• Contribute to the continuous improvement of MLOps practices and advocate for automation and scalability across the ML lifecycle.

Benefits

• Great compensation package and bonus plan
• Core benefits including medical, dental, vision, and matching 401K
• Flexible work environment, ability to work remote, hybrid or in-office
• Flexible time off including volunteer time off, vacation, sick and 12-paid holidays

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level