Experian Health is looking for an experienced MLOps Engineer to build and scale machine learning solutions that address critical challenges in the healthcare revenue cycle.
Requirements
- 3+ years' 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)
- Proficiency with containerization and orchestration tools (Docker, Kubernetes/EKS).
- 3+ years' experience with ML lifecycle tools such as MLflow, TensorFlow Serving, or Kubeflow and with CI/CD pipelines, infrastructure as code (e.g., Terraform, CloudFormation), and monitoring/logging tools
- Exposure to NLP, Bayesian modeling, or real-time ML systems
- AWS certifications (e.g., Machine Learning Specialty, DevOps Engineer)
Responsibilities
- Develop 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
- Improve 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)
Other
- Bachelor's degree in Computer Science, Engineering, Data Science, or a related field
- Experience in the healthcare domain, especially with claims or EHR data, and familiarity with standards like ICD and CPT
- Familiarity with Agile development methodologies
