Own machine learning systems end to end, from problem definition and modeling through production deployment and ongoing improvement.
Build, deploy, and maintain production-grade ML systems in Python with a strong focus on reliability, observability, and maintainability.
Solve meaningful, real-world problems by applying machine learning in practical, scalable ways that directly support users and the business.
Iterate based on real-world feedback and model performance, continuously improving systems after they’re live in production.
Partner closely with Product, Engineering, and Operations to align on goals, constraints, and success metrics.
Make thoughtful tradeoffs in ambiguous situations, prioritizing clarity, simplicity, and long-term maintainability.
Contribute to a healthy, low-ego team environment that values empathy, growth, and mutual respect, while fostering collaboration, learning, and knowledge-sharing

Bachelor’s degree in Computer Science or a related field, or equivalent practical experience.
4+ years of experience building and shipping machine learning or data-driven systems in real-world environments.
Strong Python experience in production, including building services, pipelines, or model-backed APIs.
Solid understanding of machine learning fundamentals and how to apply them pragmatically to product problems.
Experience working with data stores and pipelines (SQL databases, data warehouses, or similar).
Comfortable collaborating in a modern cloud environment (AWS or GCP), including CI/CD and deployment workflows.

Senior Machine Learning Engineer

Key skills