Staff MLOps Engineer

Job Summary

To support the development of a robust AI/ML platform, the full-time Staff MLOps Engineer will manage the architecture and implementation of machine learning infrastructure, focusing on model training, serving, and monitoring, while collaborating closely with cross-functional teams in a remote environment.

Key responsibilities

• Audit and enhance the existing AI/ML training and serving setup, making decisions on what to build or rebuild
• Develop a shared AI/ML platform that facilitates the entire ML lifecycle, ensuring rapid model iteration for Data Scientists
• Implement monitoring and observability solutions for model performance, including data drift and accuracy metrics

Required qualifications

• Proven experience leading ML platform initiatives at scale
• Strong expertise in Databricks, Kubernetes, and cloud environments (preferably AWS)
• Proficiency in programming languages such as Python, Scala, or Java
• Deep understanding of ML observability, feature stores, and model registries
• Experience in mentoring and developing engineering best practices within teams