Senior Machine Learning Engineer
Circadia Health3 months ago
El Segundo, CA, USASenior
Base Salary
$150k - $240k/yr
Responsibilities
- Design, train, and evaluate clinical prediction models using physiological time-series data and structured EHR context.
- Define prediction targets with clinical teams and build workflows for label adjudication and ground-truth assessment.
- Build evaluation harnesses, backtesting systems, and regression suites for model versions and configurations.
- Evaluate sensitivity, specificity, lead time, alert burden, calibration, class imbalance, and temporal leakage.
- Analyze model robustness across facilities, care settings, and demographic groups.
- Support model serving and deployment, monitor real-world performance, and contribute to validation studies and regulatory submissions.
- Present model behavior and limitations to non-technical stakeholders.
Requirements
- 5+ years of experience building machine learning models that reached production and were used for real decisions.
- Strong Python skills, modern deep learning framework experience, and fluency in classical machine learning.
- Experience working with time-series or sequential data.
- Experience evaluating calibration, class imbalance, and temporal leakage.
- Experience building evaluation, backtesting, or model regression infrastructure.
- Strong SQL skills and experience with production data.
- Preferred experience in healthcare ML, clinical prediction, EHR data, physiological signals, or early-warning systems.
- Preferred experience with model validation for regulatory submissions or subgroup analysis in clinical settings.
- Preferred first-author publications, significant open-source work, competition results, or a high-bar research or engineering background.
Categories
About Circadia Health
Circadia Health builds an FDA-cleared contactless patient monitoring system and software for hospitals, post-acute, and telehealth providers to flag clinical deterioration early. Its wall-mounted sensor tracks respiratory rate from up to 8 feet without wearables, with AI risk alerts reviewed by a virtual nursing team around the clock. Founded in 2016 and based in Los Angeles, it is privately held and sells devices and remote monitoring services to healthcare organizations.