Senior Software Engineer, Machine Learning

SmarterDx is a company that builds clinical AI to transform how hospitals translate care into payment. They are seeking a Senior Machine Learning Engineer to build a best-in-class ML ecosystem and work closely with various teams to advance their product suite.

Responsibilities:

• Build and scale machine-learning driven features across multiple products
• Design reusable architecture that powers and accelerates machine learning development across the company
• Deploy and maintain machine learning models and pipelines in production environments
• Work closely with data scientists, data engineers, and application engineers to integrate ML models into the broader SmarterDx platform
• Build tools to improve the lives of our data scientists
• Contribute to the design and architecture of our ML systems

Requirements:

• • 5+ years of development experience with a focus on Machine Learning and Engineering roles
• Strong proficiency in Python and SQL, with experience in machine learning libraries (Pytorch, Tensorflow)
• Experience with managing the full model production lifecycle, including deployment, release, and post-launch monitoring
• Experience working with a diverse, cross-disciplinary team to integrate machine learning into product features
• 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
• 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