MLOPS Machine Learning Operations Engineer

As an MLOps professional, your role involves focusing on efficiency, scalability, and risk reduction in the development and deployment of machine learning models. You will play a crucial part in achieving faster model development, delivering high-quality ML models, and ensuring speedy deployment and production. Additionally, you will be responsible for overseeing, controlling, managing, and monitoring thousands of models for continuous integration, delivery, and deployment, thus ensuring vast scalability and efficient management. Key Responsibilities: - Ensure reproducibility of ML pipelines for seamless collaboration across data teams - Reduce conflict with devops and IT by facilitating tightly-coupled collaboration - Accelerate release velocity by streamlining processes and workflows - Enable greater transparency and faster response to regulatory scrutiny and drift-check requests - Ensure compliance with organizational or industry policies for risk reduction Qualifications Required: - Minimum of 2 years of total work experience in the field (Preferred) You will be working full-time during the day shift at the designated in-person work location.,