Staff Software Engineer, Machine Learning

SmarterDx is a clinical AI company transforming how hospitals translate care into payment. They are seeking a Staff Machine Learning Engineer to build a best-in-class ML ecosystem that enhances their product suite with clinical AI, focusing on reliable systems and developer experience.

Responsibilities:

• Craft, implement, and maintain MLOps tools and practices, including continuous integration, delivery, and monitoring of machine learning systems
• Optimize model performance and scalability, ensuring high reliability and efficiency
• Build tools to improve the lives of our data scientists
• Contribute to the design and architecture of our ML systems

Requirements:

• 10+ years of development experience with a focus on Machine Learning and MLOps roles
• Strong proficiency in Python and SQL, with experience in machine learning libraries (Pytorch, Tensorflow)
• Experience with deploying and managing ML models in production environments, including familiarity with Docker, Kubernetes, or similar technologies
• Understanding of CI/CD best practices for machine learning, including automated testing and deployment pipelines
• Experience with cloud platforms (preferably AWS) and their machine learning services
• Experience project managing a small team using a modern agile methodology
• Experiencing influencing a cross-disciplinary organization to adopt best practices
• Familiarity with infrastructure as code (e.g., CDK, Terraform) and configuration management tools
• Strong understanding of data engineering and architecture principles
• Excellent collaboration and communication skills, with a passion for solving challenging problems in a team environment
• You're a former startup founder, or have been the first engineering hire at a startup
• Experience in the health tech domain, particularly in hospital billing systems
• Experience with end-to-end machine learning project lifecycle, from data collection and model training to deployment and monitoring
• Deployment of LLM systems into Production environments
• Contributions to open-source projects or active participation in the machine learning community