Senior Machine Learning Engineer, Function

• You enjoy working on complex, real-world problems where data is messy, signals are subtle, and correctness matters. You care about model behavior in production and value interpretability, reliability, and maintainability over quick wins
• You’re comfortable collaborating cross-functionally and communicating clearly about tradeoffs, limitations, and failure modes
• 3+ years of experience building and deploying machine learning systems in production
• Strong proficiency in Python and ML frameworks, such as PyTorch, TensorFlow, and scikit-learn (PyTorch is preferred)
• Experience with the full model lifecycle: training, evaluation, deployment, and monitoring
• Familiarity with multimodal and/or longitudinal/time-series data (tabular biomarkers, imaging-derived features, events over time, etc.)
• Solid understanding of feature engineering, model validation, error analysis, and basic statistical thinking
• Ability to collaborate effectively with data engineering and data scientists in shared data environments

Desirable

• Function’s newly launched Medical Intelligence Lab (MIL) is charged with building the operating system that converts individual and population health data into health guidance
• In essence, MIL is building a GPS for health — a system which understands where you have been, has mapped the health landscape around you, and steers you where you need to go to avoid disease and arrive at healthy longevity
• MIL brings together engineers, scientists, physicians, and regulatory and operations experts to build medical world models, prediction models, and guidance models that combine the best of human and machine intelligence
• As a Machine Learning Engineer in MIL, you will build machine learning (ML) systems that analyze large-scale, multi-modal, longitudinal health data to generate actionable insights for Function users
• These ML systems will identify connections between disparate types of data and will analyze the trajectory of that data over time to provide early warning of disease
• You will collaborate closely with data engineers, data scientists, and clinical domain experts to ensure that ML systems are reliable, interpretable, and suitable for use in regulated settings involving protected health information
• Develop, train, evaluate, and deploy machine learning models using multimodal healthcare data (e.g., blood biomarkers, images, medical records)
• Partner with data scientists and domain experts to translate clinically informed cohorts, labels, and features into ML-ready representations
• Build and own end-to-end ML workflows, including literature review/prototyping, feature generation, training/validation, inference, experiment tracking and reproducibility, deployment, and monitoring/drift detection
• Design modeling approaches for longitudinal healthcare data, capturing temporal patterns and handling evolving data distributions
• Define evaluation frameworks that prioritize robustness, calibration, interpretability, and stability across cohorts and time
• Contribute to best practices around responsible ML in healthcare, including documentation, auditability, and collaboration with clinical stakeholders
• Support experimentation while maintaining production-quality engineering standards
• As a Machine Learning Engineer at Function Health, you will be part of a tight-knit team working to build the future of health
• You’ll work on foundational ML systems that enable the next generation of health insights — with an emphasis on responsibility, rigor, and long-term impact