Senior Machine Learning Software Engineer

Responsibilities

• Leverage proprietary and open-source tools and frameworks to develop ML systems and software applications.
• Design and implement scalable and modular software architectures, emphasizing maintainability and extensibility.
• Develop core capabilities for ML training, development, deployment and monitoring.
• Develop integrations with health system applications (e.g. Epic), systems and both on-prem and cloud infrastructure.
• Responsible for continuous integration and continuous delivery of production code.
• Independently lead and execute moderately complex projects with minimal oversight.
• Contribute to the deployment and monitoring of ML capabilities based on emerging technologies, trends and methodologies.
• Lead the design and development of tools for active monitoring of models and ML applications.
• Help maintain and optimize production models and applications.
• Work with ML and data engineers to build robust and maintainable data pipelines for model development, validation, and deployment.
• Ensure seamless data integration and flow with health system applications that supports the scalability and efficiency of ML models and analytics platforms.
• Collaborate with a multidisciplinary team, including data scientists, data and ML engineers, clinicians, administrators, and product managers to define project requirements and develop solutions that meet organizational needs.
• Provide subject matter expert review, guidance and consultation.
• Demonstrate a commitment to continuous learning and professional development.
• Stay current with emerging industry trends, best practices, and technologies in ML software engineering.
• Model a culture of performance excellence both within team and across the enterprise.
• Look for opportunities to optimize the team’s processes and workflows.

Qualifications

• Bachelor's degree is required. Computer science or a related field with a focus on machine learning or data science.
• 3+ years of experience and expertise in software engineering and infrastructure to support development and deployment of machine learning models and applications is required.
• Proven track record of leading and executing moderately complex projects with minimal oversight is required.
• 1+ years healthcare analytics experience is preferred.