OpenNetworks · 6 hours ago
AI Operations (MLOps)
United States
Full-time
Remote
Mid Level
3+ years expOpenNetworks is a healthcare technology platform transforming American healthcare by creating an open marketplace that connects providers and purchasers. They are seeking a highly skilled AI Operations Engineer to build, deploy, and manage machine learning models, ensuring their reliability and scalability in a production environment.
Hospital & Health Care
Responsibilities
Educate and evangelize AI to boost productivity across all internal groups
Build scalable, high-availability models from claims, contracts, employer, employer and price transparency data to create intelligence and handle real-time inference requests for the OpenNetworks platform
Manage and optimize the underlying cloud infrastructure (compute, storage, and networking) for both large-scale model training and high-throughput serving environments
Proficient in using rapid coding techniques to create POCs to demonstrate new AI capabilities
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
Ensure all MLOps practices and data handling adhere strictly to healthcare regulatory standards, including HIPAA and data privacy best practices
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
Continuously evaluate and implement technologies to improve the speed, cost-efficiency, and reliability of the overall ML system
Qualification
Required
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
Preferred
Experience working in the HealthTech or FinTech industries, particularly with highly regulated data
Experience designing and managing data pipelines (ETL/ELT) for ML features
Knowledge of data governance, security principles, and compliance requirements in healthcare (e.g., HIPAA)
Experience optimizing models for latency and throughput (e.g., ONNX, model quantization)
Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field
Company
OpenNetworks
OpenNetworks™ envisions a future where healthcare is driven by collaboration, transparency, and innovation.
11-50 employees
Funding
Current Stage
Early StageCompany data provided by crunchbase