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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer - **Company:** Circadia Health - **Location:** El Segundo, CA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Python (Programming Language), Machine Learning, Open Source Technology, Operational Databases, Standard Sql, Feature Engineering, Deep Learning, Model Validation, Machine Learning Operations - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/senior-machine-learning-engineer-circadia-health-9000220 ## About the Role * 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 ## Description * Model development. Design, train, and evaluate clinical prediction models, with feature engineering across physiological time series and structured EHR context. * Labels and ground truth. Define what you are actually predicting with clinical teams, build adjudication workflows, and understand the noise in your targets. * Evaluation and testing infrastructure. Build the eval harnesses, backtesting, and regression suites that let us ship new model versions and new configurations with confidence, including how flagging behaves and whether explanations hold up. * Clinical evaluation. Sensitivity, specificity, lead time, and alert burden as the care team experiences them. Threshold selection is a clinical decision as much as a statistical one. * Robustness. Find where performance varies across facilities, settings, and demographics, and quantify it. * Production and evidence. Ship with ML Ops support on serving and deployment, monitor real-world performance, and contribute to validation studies and regulatory submissions., * 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, competition results, or a high-bar research or engineering background 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. ## Related Videos - [Getting Started with Machine Learning](https://www.wearedevelopers.com/videos/260-getting-started-with-machine-learning) - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [How building an industry DBMS differs from building a research one](https://www.wearedevelopers.com/videos/768-how-building-an-industry-dbms-differs-from-building-a-research-one) - [What non-automotive Machine Learning projects can learn from automotive Machine Learning projects](https://www.wearedevelopers.com/videos/397-what-non-automotive-machine-learning-projects-can-learn-from-automotive-machine-learning-projects) - [How Machine Learning is turning the Automotive Industry upside down](https://www.wearedevelopers.com/videos/61-how-machine-learning-is-turning-the-automotive-industry-upside-down) - [Machine learning 101: Where to begin?](https://www.wearedevelopers.com/videos/1014-machine-learning-101-where-to-begin) ## Related Articles - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [How machine learning can help us tell fact from fiction](https://www.wearedevelopers.com/magazine/509-how-machine-learning-can-help-us-tell-fact-from-fiction) - [Everything a Developer Needs to Know About MCP with Neo4j](https://www.wearedevelopers.com/magazine/604-everything-a-developer-needs-to-know-about-mcp-with-neo4j)