Description
The Senior MLOps Engineer will support cross-functional teams in designing, deploying, and operating machine learning solutions across the full ML lifecycle. Responsibilities include building and scaling ETL pipelines, model serving, training environments, orchestration systems, monitoring, alerting, automated testing, reusable frameworks, cloud infrastructure, cost management, and documentation. The role requires MLOps or DevOps experience, a bachelor’s degree in a quantitative field, at least three years of Machine Learning Engineer experience, and expertise with cloud platforms, CI/CD, infrastructure as code, distributed computing, Python, and machine learning libraries.
