Machine Learning Engineer, WHOOP

• Bachelor’s degree in Computer Science, Machine Learning, Applied Mathematics, Statistics, or a related field
• 2+ years of professional experience delivering ML-driven solutions in production environments
• Proficient in Python with experience using ML libraries (e.g., scikit-learn, PyTorch, TensorFlow) and numerical packages (e.g., numpy, scipy, pandas)
• Knowledge of software development best practices including Git, testing, CI/CD, and Docker
• Experience operating ML services in production, including monitoring, alerting, and troubleshooting
• Exposure to tools and platforms for ML infrastructure (e.g., Airflow, MLflow, AWS/GCP, Kubernetes)
• Excellent communication skills with the ability to collaborate effectively across technical and non-technical teams

Desirable

• As a Machine Learning Engineer II on our Health Insights team, you will help develop and deploy machine learning systems that deliver meaningful, personalized health metrics to millions of members
• You will work at the intersection of data science, backend engineering, and health research, contributing to scalable ML solutions built on physiological and behavioral data streams
• This role emphasizes robust system design, performance, and reliability in production
• Architect and optimize ML systems and models to ensure efficiency and scalability in production environments
• Design, implement, and maintain scalable machine learning inference pipelines that power core health features
• Deploy models and build robust backend services that integrate seamlessly with the WHOOP platform
• Collaborate closely with MLOps and software engineering teams to ensure reliable deployment, monitoring, and infrastructure support for model serving
• Establish and uphold performance, observability, and accuracy standards through rigorous testing, validation, and continuous evaluation