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ML Ops Engineer

circadiahealth · El Segundo
Full-timeEngineeringHealthcare$179,000–$241,000/yr
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About the ML Operations Engineer role

ML Operations Engineer positions focus on delivering results in their domain. This page aggregates open ML Operations Engineer roles and what employers typically expect.

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.

Salary estimate

$179,000 – $241,000/yr
Provided by the employer.

Skills for this role

Ci/CdMachine Learning

Resume tips for ML Operations Engineer applicants

Interview preparation

Prepare concrete STAR-format stories that show ML Operations Engineer outcomes you drove.

Research the employer's product and recent news before the interview.

Be ready to explain how you'd approach a typical ML Operations Engineer problem end to end.

Have thoughtful questions ready about the team, tools and success metrics.

About circadiahealth

circadiahealth is actively hiring on Jobedly. Explore their open roles and what it's like to work there.

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