MLOps & Infrastructure Engineer
Location:
Remote / Flexible
About the Role:
Set up and manage the ML and LLM deployment infrastructure for a globally distributed healthcare AI platform. Interested in this role? Contact the Careverse team at https://careverse.us/contact-us to confirm recruitment status, location, employment terms, and application instructions. Mention the role title and share a professional introduction. Do not include sensitive personal or health information.
Responsibilities:
- Build pipelines for training, validation, deployment, and monitoring of ML/LLM models.
- Automate fine-tuning and retraining with secure patient data (in compliance with privacy standards).
- Implement A/B testing, feedback loops, and live performance tracking.
- Monitor and auto-scale models based on usage and region.
Requirements:
- 4+ years in DevOps/MLOps or infrastructure engineering.
- Experience with MLFlow, Weights & Biases, Ray, Kubernetes, and scalable GPU deployment.
- Familiarity with secure healthcare deployments (encryption, data locality, compliance).
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