Principal AI/ML Engineer - AI Program

Responsibilities

• Provide strategic direction and technical leadership for AI Engineering initiatives.
• Work with leadership team to define the AI roadmap and prioritize projects aligned with organizational objectives.
• Lead component design, development, integration, and standardization to create AI-driven solutions that seamlessly integrate into clinical practice to enhance patient care and clinic operations.
• Lead the collaboration with multidisciplinary teams, including clinicians, user experience designers, product managers, and IT professionals, to understand user needs, workflows, and clinical requirements and assess feasibility. Translate user feedback and requirements into design concepts and usability specifications for AI solutions.
• Lead the interpretation of data analysis to guide strategic choices and clarify complex insights for non-technical users to connect AI technologies and clinical applications.
• Lead consultative services to clinical work units or AI product teams, offering insights and strategies to address complex business problems.
• Leverage machine learning techniques such as deep learning, natural language processing, computer vision, large language models, etc., to lead the design, development, and deployment of end-to-end AI solutions for healthcare applications. This includes evaluating and guiding architectural choices involving vision encoders, multimodal fusion approaches, representation learning, and model adaptation strategies.
• Establish rigorous evaluation methodologies and performance metrics to assess the effectiveness, usability, and impact of AI solutions in real-world healthcare settings.
• Ensure compliance with ethical guidelines, regulatory requirements, and data privacy standards in the development and deployment of AI solutions by the AI development team.
• Oversee the engineering of systems crucial for developing and deploying AI solutions.
• Facilitate consistent and automated AI software solution development and releases through the design, testing, and maintenance of tools and associated CI/CD pipelines.
• Define and implement best practices and standards for AI development and deployment methodologies, tools, and platforms.
• Mentor, guide, and lead junior engineers within the AI enablement team. May have supervisory responsibilities.
• Foster a culture of collaboration, innovation, and knowledge sharing across the organization.
• Support talent development initiatives, including training programs, technical workshops, and skill-building activities to enhance team capabilities.
• Contribute to the development of new AI methods and technologies that can advance the state-of-the-art in healthcare AI, including novel approaches in multimodal learning, foundation models, representation learning, computer vision, and clinical AI evaluation.
• Publish and present the results of AI development and translation in peer-reviewed journals and conferences.

Qualifications

• A master’s degree in engineering, computer science, mathematics, health science, or a related field with 7 years of relevant experience, or a bachelor’s degree with 9 years of relevant experience.
• Extensive (7+ years) experience applying AI and machine learning in production healthcare environments or similar highly regulated or technology focused industries, showcasing an acute understanding of healthcare technology.
• Demonstrated leadership in managing complex projects, with a proven ability to navigate intricate project requirements and deliver successful outcomes.
• Proven success in fostering collaboration across diverse teams and effectively communicating complex technical concepts to non-technical stakeholders.
• Expertise in cloud infrastructure environment and software development tools.
• Experience working with large, complex, and heterogeneous data sets, preferably in healthcare.
• Strong skills in AI/ML techniques and frameworks.
• Expertise with best practices in data engineering, data science, AI Engineering, and the MLOps communities.
• In-depth knowledge of healthcare domain, including clinical workflows, electronic health records, medical terminologies, regulatory requirements, and industry standards.
• Demonstrated leadership in administration, education, software development, and technical reporting.
• Experience mentoring and training less-experienced team members, coupled with strong interpersonal, communication, and time management skills.