Senior Machine Learning Engineer

Circadia Health • El Segundo, CA

1d • $135,000 - $220,000 • Onsite

About The Position

At Circadia Health, a growth-stage healthcare AI company, the Senior Machine Learning Engineer plays a pivotal role as the model is the product itself. This position is responsible for the end-to-end ownership of clinical prediction models, including their predictions, evaluation methods, threshold settings, and deployment. The role leverages a unique dataset of continuous vital signs and clinical records from a large patient population. The engineer will define predictions in collaboration with clinical teams, build adjudication workflows, and understand the nuances of imperfect labels derived from retrospective chart review. This is a critical position where the accuracy of the models directly impacts the platform's overall delivery and the care decisions for tens of thousands of seniors daily.

Requirements

• 5+ years building ML models that reached production and were used for real decisions
• Strong Python and modern deep learning frameworks, plus fluency in classical ML
• Experience with time-series or sequential data
• Evaluation practice covering calibration, class imbalance, and temporal leakage
• Experience building evaluation, backtesting, or model regression infrastructure
• Strong SQL and experience with production data
• Experience presenting model behavior and limitations to non-technical stakeholders

Nice To Haves

• Healthcare ML, clinical prediction, EHR data, physiological signals, or early-warning systems
• Model validation supporting regulatory submission, or subgroup analysis in a clinical setting
• First-author publications, significant open source contributions, competition results, or a high-bar research or engineering background

Responsibilities

• Model development: Design, train, and evaluate clinical prediction models, including feature engineering across physiological time series and structured EHR context.
• Labels and ground truth: Define prediction targets with clinical teams, build adjudication workflows, and understand the noise in target labels.
• Evaluation and testing infrastructure: Build evaluation harnesses, backtesting systems, and regression suites for confident deployment of new model versions and configurations, including flagging behavior and explanation validity.
• Clinical evaluation: Assess model performance using metrics like sensitivity, specificity, lead time, and alert burden from the perspective of the care team, and participate in threshold selection.
• Robustness: Identify and quantify performance variations across different facilities, settings, and demographics.
• Production and evidence: Ship models with ML Ops support for serving and deployment, monitor real-world performance, and contribute to validation studies and regulatory submissions.

Benefits

• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed