Senior ML Ops Engineer

Circadia Health; El Segundo (CA); On-site; USD 150,000 - 220,000; Full time

Benefits offered by this job

Stock options

100% company-paid medical, dental, and

vision coverage

401(k)

Generous vacation and sick leave

Job summary

Circadia Health in El Segundo, CA is seeking a Senior ML Ops Engineer to own end-to-end ML pipelines, production deployment, and monitoring. You will work with the ML engineering team to push models from development to production while ensuring reliability and cost efficiency.

You will design and maintain orchestration, deployment, and lineage systems on AWS, with emphasis on model monitoring and compliance.

Qualifications

• 4+ years in MLOps, ML engineering, DevOps, or related infrastructure role.
• Strong Python for pipeline development and automation.
• Hands-on with Airflow and a model registry such as MLflow.
• Experience deploying ML workloads on AWS (Batch, EC2, S3, IAM, CloudWatch).
• Containerization, infrastructure-as-code, SQL, and Snowflake.
• Building monitoring and alerting for production systems.
• Experience collaborating with ML engineers on model development.

Responsibilities

• Pipeline orchestration: Training, evaluation, and deployment workflows in Airflow with automated retraining and rollback.
• Deployment and release: Models onto AWS Batch with versioning and canary/shadow releases.
• Tracking and lineage: MLflow registry, metadata conventions, dataset versioning for reproducibility.
• Monitoring and drift: Alerting for degradation and prediction quality on clinically important models.
• ML compute and cost: AWS compute for training/inference, IaC, and cost optimization.
• Hands-on model work: Contribute to model development alongside the ML engineering team.
• Compliance: HIPAA and SOC 2 adherence in pipelines and PHI handling.

Job description

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

$150,000 - $220,000 a year

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.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.