Principal Machine Learning Software Engineer

DescriptionPenn Medicine is dedicated to our tripartite mission of providing the highest level of care to patients, conducting innovative research, and educating future leaders in the field of medicine. Working for this leading academic medical center means collaboration with top clinical, technical and business professionals across all disciplines.Today at Penn Medicine, someone will make a breakthrough. Someone will heal a heart, deliver hopeful news, and give comfort and reassurance. Our employees shape our future each day. Are you living your life's work?Entity: CorporateDepartment: PennDNA Data ScienceLocation: 3600 Civic Center BlvdHours: 8hr DaysSummary:• The University of Pennsylvania Health System (UPHS) is seeking a Principal Machine Learning Software Engineer to join our Data and Analytics team, Penn DnA. In this role, you will be responsible for the development, implementation, and maintenance of cutting-edge software for machine learning models and algorithms to drive impactful insights and solutions across various healthcare domains. This role entails collaborating closely with cross-functional stakeholders and advancing our organization's data-driven initiatives to enhance patient care, operational efficiency, and research endeavors. The ideal candidate will have a strong background in software engineering, machine learning infrastructure, deep understanding of healthcare data and mentoring of junior members of a team. The Principal Machine Learning Software Engineer will report to the Head of Machine Learning.Responsibilities:• Leadership & Strategy: Provide strategic direction and technical leadership for the machine learning software engineering, guiding the development and execution of innovative software standards and solutions for ML initiatives. Define and evangelize the long-term vision and technical standards for software engineering initiatives, aligning them with organizational objectives and industry best practices. Establish technical standards for Penn Medicine’s AI governance and review of both vendor and internal capabilities.• Systems and Software Engineering: 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. Develops 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 leads multiple complex and long-term projects from concept to execution. Produces client-ready/production-capabilities.• Model Deployment and Monitoring: Develop and enforce the technical standards for deployment of machine learning models healthcare applications. Lead technical evolution of 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. Leads the specification and development of infrastructure for MLOps, including deployment, performance monitoring, automated training, etc.. Maintain and optimize production models and applications.• Data Sourcing and Integration: Work with ML and data engineers to build robust and maintainable data pipelines for model development, validation, and deployment. Work closely with ML and data engineers to design software for robust and maintainable data pipelines. Ensure seamless data integration and flow with health system applications that supports the scalability and efficiency of ML models and analytics platforms.• Collaboration: Collaborate with a multidisciplinary team, including data scientists, data and ML engineers, clinicians, administrators, and product managers to understand project requirements, identify strategic opportunities and develop solutions that meet organizational needs. This collaboration aims not only to advance healthcare technology but also to drive significant improvements in patient outcomes and operational efficiencies, demonstrating the tangible impact of our work. Provide subject matter expert review, guidance and consultation. Leads through influence, enlisting the help of others across the enterprise, as needed, and manages project execution. Trusted to represent Penn DnA with senior internal clients and expected to build relationships with senior leaders.• Continuous Improvement: Stay current with emerging industry trends, best practices, and technologies in machine learning engineering. Model a culture of performance excellence both within team and across the enterprise. Mentor and coach more junior team members, fostering a collaborative and high-performance culture. Actively seeks and applies feedback from others to strengthen capabilities.Education or Equivalent Experience:• Bachelor of Arts or Science computer science, software engineering, or a related field (Required)• And 7+ years Experience in software engineering, software development, and machine learning. Proven track record of independently leading projects from concept to execution, coordinating with cross-functional teams, as needed.• Master of Arts or Science computer science, software engineering, or a related field (preferred)We believe that the best care for our patients starts with the best care for our employees. Our employee benefits programs help our employees get healthy and stay healthy. We offer a comprehensive compensation and benefits program that includes one of the finest prepaid tuition assistance programs in the region. Penn Medicine employees are actively engaged and committed to our mission. Together we will continue to make medical advances that help people live longer, healthier lives.Live Your Life's WorkWe are an Equal Opportunity and Affirmative Action employer. Candidates are considered for employment without regard to race, ethnicity, color, sex, sexual orientation, gender identity, religion, national origin, ancestry, age, disability, marital status, familial status, genetic information, domestic or sexual violence victim status, citizenship status, military status, status as a protected veteran or any other status protected by applicable law.