AI Operations – MLOps
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Job Description
AI Operations Engineer at OpenNetworks enhancing healthcare technology through MLOps and machine learning systems. Building, deploying, and managing ML models for efficient and reliable healthcare delivery.
Responsibilities:
- Educate and evangelize AI to boost productivity across all internal groups
- Build scalable, high-availability models from claims, contracts, employer and price transparency data to create intelligence and handle real-time inference requests
- Manage and optimize the underlying cloud infrastructure for both large-scale model training and high-throughput serving environments
- Implement advanced monitoring and alerting systems to track model performance, data drift, and prediction latency in production
- Establish processes for model versioning, lineage tracking, and rollback capabilities to ensure operational integrity and auditability
- Collaborate directly with the Data Science team to containerize model code, optimize models for production serving efficiency, and transition models from research to production-readiness
- Automate all aspects of the model lifecycle, from data ingestion and feature engineering to deployment and retraining triggers
Requirements:
- 3+ years of experience in MLOps, DevOps, or Software Engineering with a focus on machine learning systems
- Expert proficiency in Python and solid experience with writing clean, production-level code
- Strong experience with a major cloud provider (AWS, GCP, or Azure) and expert knowledge of containerization technologies (Docker, Kubernetes)
- Hands-on experience with MLOps frameworks and platforms (e.g., MLflow, Kubeflow, Sagemaker, TFX, or similar)
- Deep understanding of the machine learning lifecycle, from data prep and model training to deployment and monitoring
- Bachelor's or Master’s degree in Computer Science, Engineering, or a related technical field
Benefits:
- Health insurance
- Retirement plans
- Paid time off
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