Schneider is seeking an AI & Machine Learning Engineer in Green Bay, Wisconsin to design and develop AI-driven software solutions addressing business problems. The AI & Machine Learning Engineer will work closely with senior engineers and data scientists to develop and maintain software solutions for data science initiatives. Responsibilities include deploying and monitoring machine learning models in production (on-premises and in cloud environments), developing data processing and feature engineering pipelines, building APIs and microservices to support machine learning models, implementing model performance monitoring and drift detection, writing high-quality, efficient and well-documented code, conducting code reviews and mentoring junior engineers on software development best practices, and performing data analysis to generate insightful reports to support business decisions. Qualifications include a bachelor's degree in computer science, software engineering, data science, or related field; at least 2 years of experience in software engineering or data science; proficiency in Python, Java or C++; knowledge of data science libraries (Pandas, NumPy, Scikit-learn); understanding of ML concepts, algorithms, model evaluation metrics and feature engineering; experience with SQL and database management in a Linux environment; proficiency with version control (Git); familiarity with cloud platforms (Azure, AWS, Google Cloud); experience with container platforms (Docker, Kubernetes), streaming platforms (Apache Kafka), ML Ops tools (MLflow), and CI/CD concepts. The role offers

Schneider is seeking an AI & Machine Learning Engineer in Green Bay, Wisconsin to design and develop AI-driven software solutions addressing business problems. The AI & Machine Learning Engineer will work closely with senior engineers and data scientists to develop and maintain software solutions for data science initiatives. Responsibilities include deploying and monitoring machine learning models in production (on-premises and in cloud environments), developing data processing and feature engineering pipelines, building APIs and microservices to support machine learning models, implementing model performance monitoring and drift detection, writing high-quality, efficient and well-documented code, conducting code reviews and mentoring junior engineers on software development best practices, and performing data analysis to generate insightful reports to support business decisions. Qualifications include a bachelor's degree in computer science, software engineering, data science, or related field; at least 2 years of experience in software engineering or data science; proficiency in Python, Java or C++; knowledge of data science libraries (Pandas, NumPy, Scikit-learn); understanding of ML concepts, algorithms, model evaluation metrics and feature engineering; experience with SQL and database management in a Linux environment; proficiency with version control (Git); familiarity with cloud platforms (Azure, AWS, Google Cloud); experience with container platforms (Docker, Kubernetes), streaming platforms (Apache Kafka), ML Ops tools (MLflow), and CI/CD concepts. The role offers