Responsibilities
- Design, build, test, and maintain machine learning systems using robust software engineering principles.
- Convert experimental data science models into reliable, scalable production systems.
- Manage full-cycle machine learning workflows, applying MLOps standards across cloud and on-premises environments.
- Work closely with data scientists, engineers, and product teams across international locations in cross-functional settings.
- Improve engineering quality by developing and promoting advanced tools, techniques, and best practices for ML systems.
- Support team growth through mentoring, knowledge sharing, participation in internal communities, and cross-functional learning.
- Help define the future of ML engineering by contributing to strategic planning and shaping technical roadmaps.
Work Arrangement
Remote (Worldwide)
