ML Ops Engineer

Requirements

• 4+ years of experience in MLOps, ML Engineering, DevOps, or a closely related infrastructure role.
• Strong proficiency in Python for ML pipeline development, tooling, and automation.
• Hands-on experience with ML pipeline orchestration tools, particularly Apache Airflow.
• Experience with model registries and experiment tracking platforms (MLflow preferred).
• Experience deploying and operating ML workloads on AWS (Batch, EC2, S3, IAM, CloudWatch).
• Solid understanding of the ML lifecycle: training, evaluation, deployment, monitoring, and retraining.
• Experience with containerisation (Docker) and infrastructure-as-code.
• Proficiency with Git and version control workflows.
• Familiarity with SQL and data warehousing platforms (Snowflake preferred).
• Experience implementing monitoring, logging, and alerting for production systems.
• Strong debugging and incident response skills for complex distributed systems.

Additional Information

Position Overview As an ML Ops Engineer at Circadia Health, you will own the infrastructure and operational lifecycle of the machine learning systems that power our clinical monitoring platform. You will build and maintain the production ML pipelines, deployment infrastructure, and monitoring systems that enable Circadia's predictive models to identify early signs of clinical deterioration. Reporting to the Principal ML Engineer, you will work across ML, backend, data, and clinical teams to ensure models are reliably trained, versioned, deployed, and monitored in both cloud and edge environments. You will be a key driver in elevating Circadia's ML practice - from reproducibility and experiment tracking to CI/CD for models and operational observability. This is a high-ownership role at a lean company where production reliability, rapid iteration, and pragmatic engineering are essential. Your work will directly impact patient outcomes by ensuring our predictive models are always running, always accurate, and always improving. Why Circadia Health Circadia Health is redefining patient monitoring through contactless sensing and AI-driven clinical insights. As we scale from tens of thousands to hundreds of thousands of monitored patients, our data infrastructure is central to everything we do. You'll have the opportunity to: - Work on real-world healthcare problems with measurable patient impact - Build data systems that power clinical-grade AI and ML - Take ownership in a fast-growing, mission-driven company - Collaborate with a highly skilled, multidisciplinary team

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