- Remote, United States +1 more
- Remote
- Senior
A hands-on Applied ML Engineer to bridge the gap between machine learning research and production-ready engineering systems, taking ownership of the full deployment lifecycle from data pipelines to model serving and monitoring.
Locations (2)
- United States, United States
- Canada
Compensation
Competitive compensation: Attractive total compensation package with significant performance-based bonus potential.
Responsibilities
- Transform research-grade machine learning code and experimental prototypes into production-ready, maintainable, and scalable software systems
- Take ownership of end-to-end ML deployment pipelines, including data ingestion, feature engineering, model integration, inference, serving, monitoring, and reliability
- Work closely with machine learning researchers and engineering teams to translate research objectives and technical concepts into robust, observable production solutions
- Introduce and strengthen structured software development practices, including task management, Git workflows, code reviews, testing, and continuous integration and deployment (CI/CD)