Senior Machine Learning Engineer

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Steadily is hiring a Senior Machine Learning Engineer as the second member of its dedicated ML team in Austin, TX (4 days per week in-office). You will own the end-to-end ML lifecycle — from raw data pipelines and feature engineering to model deployment and monitoring — with focus areas like property-level risk estimation and aerial image analysis for its landlord insurance product. The role is roughly 30% lightweight data pipeline/dbt work and 70% modeling, deployment, and monitoring, offering high autonomy and direct business impact at a fast-growing, well-funded insurtech startup.

• Own the end-to-end ML lifecycle: design, build, deploy, and monitor models with emphasis on scalability, quality, and maintainability
• Build lightweight data pipelines and dbt tables to make raw data model-ready (no heavy ETL ownership)
• Lead exploration of new ML applications to predict risk at the per-insured and portfolio level
• Write clean, maintainable code in an event-driven stack (Kafka, AWS EKS, Python, Django/FastAPI, Postgres) with CI/CD via GitHub Actions
• Partner with Engineering, Product, Operations, and Business teams to ensure models solve real-world problems
• Provide metrics and visibility into model quality, bias, and performance with scientific rigor

• 5+ years applying machine learning methods to production problems