Machine Learning Engineer

Position Responsibilities:

Design, build, and maintain Continuous Integration/Continuous Development (CI/CD) pipelines for machine learning models
Deploy and manage ML models in production environments using containerization and orchestration technologies
Implement monitoring, logging, and alerting solutions to track model performance, system health, and data drift
Collaborate with data scientists to understand model requirements and optimize the process of transforming models from development to a production-ready state
Create and maintain technical documentation for ML Operations (Ops) processes, infrastructure, and deployments
Define ML/Artificial Intelligence (AI) governance to ensure data security and ethical standards are met for all modeling processes
Travel up to 5% of the time
Other duties as assigned

Required Education and Experience:

Bachelor’s degree in computer science, Data Science, Mathematics, or related quantitative discipline and 3 to 5 plus years of experience in ML Engineering, Software Engineering, or a related field or High School Diploma/General Education Diploma and 7 plus years of the above stated experience

Preferred Education and Experience:

Master’s Degree in computer science, Data Science, or other graduate education in related quantitative fields
Hands-on experience with CI/CD pipelines, automation tools, and version control systems like Azure DevOps, Github, or similar and strong understanding of machine learning concepts and the ML development lifecycle
Experience building ML Ops infrastructure and serving models via cloud platforms such as Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP)
Strong proficiency in Python and working knowledge of Bash/shell scripting for automation and system operations
Strong understanding of Structured Query Language (SQL) and experience with big data platforms, i.e., Snowflake, Databricks, or similar
Experience with Infrastructure-as-Code tools, i.e., Terraform, Azure Resource Manager, or similar

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