Senior Machine Learning Software Engineer

Entity: Corporate Services

Department: PennDNA Data Science

Location: 3600 Civic Center Blvd, Philadelphia, PA

Hours : Remote, M-F, 9-5.

Summary:

Working with a team of data scientists and ML engineers, the Senior Machine Learning Software Engineer is responsible for the development, implementation, and maintenance of cutting-edge software for machine learning models and algorithms. The goal is to drive impactful insights and solutions across various healthcare domains, such as enhancing patient care, operational efficiency, and research endeavors. The ideal candidate will be a seasoned software engineer with experience in machine learning infrastructure and healthcare data. The Senior ML Software Engineer is both a member of a team, has expertise in one or more sub-domains, triages and refines requests, leads moderately complex projects and mentors more junior members of the team.

Responsibilities:

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. 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.

Model Deployment and Monitoring: Develop and enforce the technical standards for deployment of machine learning models for healthcare applications. 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.

Data Sourcing and Integration: 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.

Collaboration: 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. 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.

Continuous Improvement: 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.

Education or Equivalent Experience:

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.

We are an Equal Opportunity 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.