Machine Learning Engineer

Position Summary We are seeking a skilled Machine Learning Engineer with approximately three years of hands-on experience designing, deploying, and maintaining production-grade machine learning systems. In this role, you will collaborate closely with data scientists, software engineers, and product teams to translate research models into reliable, scalable, and high-impact applications. You will be deeply involved in the end-to-end ML lifecycle—from data ingestion and feature engineering to deployment, monitoring, and continuous improvement—playing a critical part in shaping our machine learning platform and capabilities. This role can be located in St. Louis, MO, Boston, MA or New York, NY. Primary Responsibilities - Develop, deploy, and optimize machine learning models for real-world business use cases and client-facing applications. - Partner with data scientists to operationalize predictive models and ensure scalable, maintainable, and performant production deployments. - Design and implement data pipelines and workflows that support training, inference, and model lifecycle management. - Work with large, complex datasets to ensure data quality, reproducibility, and reliable version control across ML workflows. - Implement model monitoring, logging, and alerting strategies to track performance, detect drift, and support retraining cycles. - Leverage cloud platforms (AWS, Azure, GCP) to build scalable ML solutions using managed services and infrastructure-as-code practices. - Write clean, modular, and well-documented code aligned with MLOps and software engineering best practices. - Stay current on emerging ML tooling, frameworks, and industry best practices to continuously enhance our platform and capabilities. Qualifications - Master’s degree in Computer Science, Data Science, Engineering, or a related technical field. - 3+ years of experience in machine learning engineering, applied ML, or related software engineering roles. - Strong proficiency in Python