Senior ML Ops Engineer

Circadiahealth

El Segundo

Who this role is best for

A natural match if you have experience with healthcare AI systems and MLOps infrastructure.

Best fit for

Candidates with healthcare domain knowledge and MLOps expertise in deploying models on AWS
— “healthcare, medical devices, or clinical data systems”
Individuals with a track record of building reproducible ML workflows and managing model drift
— “tracking and lineage. MLflow registry, conventions for artifacts and metadata, and dataset versioning so training runs are reproducible”
Candidates who can manage complex infrastructure-as-code and containerization practices
— “containerization, infrastructure-as-code, SQL, and Snowflake”

Things to consider

This role requires full ownership of model degradation consequences in clinical settings
— “It surfaces as a patient who deteriorated and nobody was alerted”
Candidates must be prepared to handle HIPAA and SOC 2 compliance across all pipeline stages
— “HIPAA and SOC 2 across pipelines, with sound PHI handling in training data, artifacts, and outputs”

How to stand out

Highlight experience with real-time monitoring and alerting for production ML models
— “Monitoring and drift. Drift, prediction quality, and degradation alerting on models where degradation is clinically consequential”
Emphasize contributions to model development alongside ML engineers, not just infrastructure work
— “Hands-on model work. Contributing to model development alongside the ML engineering team, as a secondary focus behind the platform”
Showcase your ability to manage large-scale data pipelines and model training on AWS
— “Pipeline orchestration. Training, evaluation, and deployment workflows in Airflow, with automated retraining, promotion, and failure recovery”
Demonstrate your experience with automated retraining and failure recovery systems
— “automated retraining, promotion, and failure recovery”
Demonstrate your ability to handle sensitive data with compliance frameworks like HIPAA
— “sound PHI handling in training data, artifacts, and outputs”

Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · TeamLevel · Senior

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

Pipeline orchestration
Deployment and release
Tracking and lineage
ML compute and cost
Hands-on model work

Typical background

4+ years in MLOps, ML engineering, DevOps, or a closely related infrastructure role

Skills & requirements

Required

MlopsML EngineeringDevOpsPythonAirflowMlflowAWSContainerizationInfrastructure-as-codeSQLSnowflakeBuilding Monitoring And Alerting For Production Systems

Preferred

Model Serving FrameworksData Versioning ToolsHealthcareMedical DevicesClinical Data SystemsSignificant Open Source ExperienceHigh-bar Engineering Background

Stack & domain

PythonAirflowMlflowAWSContainerizationInfrastructure-as-codeSQLSnowflakeBuilding Monitoring And Alerting For Production SystemsModel DevelopmentHealthcareAI

About the role

Original posting from Circadiahealth via Lever

About Circadia Health
Circadia Health is a growth-stage healthcare AI company on a mission to prevent avoidable hospitalizations and transform senior-care operations. Our Circadia Intelligence Platform combines:
Contactless sensing that monitors respiration and motion with medical-grade accuracy
Native predictive models that detect 85% of preventable adverse events several days in advance
Enterprise integrations that operationalize predictions directly inside EHR, care-coordination, billing, and compliance workflows
Today, our technology touches 40,000+ post-acute patients daily across skilled-nursing, home-health, and home-care networks. We are backed by leading healthcare and AI investors and headquartered in El Segundo, CA.
Why this role exists:
Our models decide whether a care team walks into a room tonight. They train on 70,000 years of continuous vital signs joined to clinical records from more than 400,000 unique patients. When one of them degrades it does not surface as an error rate. It surfaces as a patient who deteriorated and nobody was alerted, which means the platform that trains, ships, and watches those models carries real clinical weight. You will own it: the pipelines, the path to production, and the monitoring that catches degradation before a clinician would.
What you'll own:
Pipeline orchestration. Training, evaluation, and deployment workflows in Airflow, with automated retraining, promotion, and failure recovery.
Deployment and release. Models onto our platform on AWS including Batch, with versioning and rollback through MLflow, maturing toward shadow and canary releases.
Tracking and lineage. MLflow registry, conventions for artifacts and metadata, and dataset versioning so training runs are reproducible.
Monitoring and drift. Drift, prediction quality, and degradation alerting on models where degradation is clinically consequential.
ML compute and cost. AWS compute for training and inference, infrastructure-as-code, and cost optimization.
Hands-on model work. Contributing to model development alongside the ML engineering team, as a secondary focus behind the platform.
Compliance. HIPAA and SOC 2 across pipelines, with sound PHI handling in training data, artifacts, and outputs.
Required Qualifications:
4+ years in MLOps, ML engineering, DevOps, or a closely related infrastructure role
Strong Python for pipeline development, tooling, and automation
Hands-on Airflow, and a model registry such as MLflow
Deploying and operating ML workloads on AWS (Batch, EC2, S3, IAM, CloudWatch)
Containerization, infrastructure-as-code, SQL, and Snowflake
Building monitoring and alerting for production systems
Enough model development experience to contribute alongside ML engineers
Preferred:
Model serving frameworks or data versioning tools
Healthcare, medical devices, or clinical data systems
Significant open source, systems that outlived your tenure, or a high-bar engineering background
Compensation:
As a full-time Senior ML Ops Engineer, you will be employed by Circadia Health, Inc. The anticipated annual base salary range for this full-time position is $150,000 - $220,000. The base range is determined by role and level, and placement within the range will depend on a number of job-related factors, including but not limited to your skills, qualifications, experience, and location.
Annual salary is only one part of an employee's total compensation package at Circadia Health. We also offer:
Meaningful employee stock options
100% company-paid medical, dental, and vision coverage
401(k)
Competitive time off with pay policies including vacation, sick days, and company holidays
Impact: your work will influence care decisions for tens of thousands of seniors every day.
Culture: hard-working, mission-driven, and collaborative — with weekly and monthly social events like yoga, beach bonfires, and Wednesday/Friday team lunches.
Circadia Health is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All employment decisions are based on business needs, job requirements, and individual qualifications, without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, veteran status, or any other status protected by law.

Source: Circadiahealth careers (Lever)