MLOps Engineer II

Job Summary

Supporting cross-functional teams in designing, deploying, and operating machine learning solutions, the full-time remote MLOps Engineer II will build scalable infrastructure and tools while collaborating with Data Scientists and Engineers throughout the machine learning lifecycle.

Key responsibilities

• Collaborate with Data Scientists and Engineers to build and scale ETL pipelines and deploy models into applications
• Design and maintain scalable machine learning infrastructure, focusing on performance and cost efficiency
• Support the development of monitoring, alerting, and automated testing frameworks for data pipelines and models

Required qualifications

• Bachelor's degree in Data Science, Computer Science, Statistics, Applied Mathematics, or a related field
• 3+ years of experience as a Machine Learning Engineer with a proven track record in production environments
• Experience in MLOps or DevOps practices, including Docker, Kubernetes, and CI/CD pipelines
• In-depth knowledge of Google Cloud Platform services, particularly Vertex AI and BigQuery
• Extensive expertise in Python and machine learning libraries such as TensorFlow and PyTorch