Full-Time MLOps Engineer (Machine Learning) (Remote)

• 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)

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

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