MLOps Engineer - Healthcare (Remote)

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.

You will:

• 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.

• 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
• 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).
• Bachelor's degree in Computer Science, Engineering, Data Science, or a related field.

Benefits/Perks:

• 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
• Explore all our exciting benefits here: https://yourexperianbenefits.com/cand-index.html

At Experian, our people and culture set us apart. We're deeply committed to creating an environment where everyone feels they belong and can excel. From inclusion and authenticity to work/life balance, development, wellness, collaboration, and recognition, we focus on what truly matters. Our people-first approach has earned us global recognition: World's Best Workplaces™ 2024 (Fortune Top 25), Great Place To Work™ 2025 in 26 countries, and Glassdoor Best Places to Work 2024, among others.

Want to see what life at Experian is really like? Explore Experian Life on social or visit our careers site.

Our compensation reflects the cost of labor across several U.S. geographic markets. The base pay range for this position is listed above. Within this range, individual pay is determined by work location and additional factors such as job-related skills, experience, and education. You will be also eligible for a variable pay opportunity.

Experian is proud to be an Equal Opportunity Employer for all groups protected under applicable federal, state and local law, including protected veterans and individuals with disabilities. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.

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