Machine Learning Engineer III – Generative AI – Windreich Department of Artificial Intelligence

Description The Windreich Department of AI & Human Health is rapidly advancing the use of technology to improve health outcomes and is at the forefront of AI implementation within the Mount Sinai Health.

Machine Learning Engineer III will oversee the design and development of sophisticated machine learning systems. They will collaborate closely with cross-functional teams to drive innovation and ensure the successful implementation of machine learning solutions.

Assume complete ownership of the entire machine learning system development process.

Coordinate closely with other team members and other engineering teams to ensure seamless integration and alignment with broader organizational goals and workflows.

Lead the collaborative efforts with cross-functional teams, including data scientists and product managers, to ensure the successful deployment and robust maintenance of machine learning models.

Oversee the continuous monitoring and timely updating of deployed models to guarantee enduring performance and reliability.

Exhibit technical leadership and mentorship to Machine Learning Engineer I, II, and other team members.

Encourage knowledge exchange and promote professional growth within the team.

Establish and enforce best practices for machine learning system development, including coding standards, code reviews, and comprehensive documentation.

Serve as the primary contact for technical inquiries related to machine learning within the team, providing expert guidance and solutions.

Utilize advanced problem-solving skills to navigate and resolve complex technical challenges and obstacles.

Foster a collaborative environment for brainstorming and implementing effective solutions with the team and other departments.

Remain up-to-date with the latest advancements and trends in the fields of software engineering and machine learning.

Conduct proactive research to uncover new methods and techniques applicable to future projects.

Lead initiatives to explore, test, and implement new technologies and frameworks, ensuring the team is always at the forefront of industry innovations.

Engage in effective communication and collaboration across various teams within the organization to ensure alignment and coordination in the execution of machine learning projects.

Facilitate transparent and timely communication with all relevant stakeholders, ensuring that all are kept informed of project statuses, challenges, and achievements.

Work collaboratively with cross-functional teams, fostering a cooperative environment for the seamless integration of machine learning systems into diverse organizational processes and workflows.

Contribute to building strong interdepartmental relationships, enabling the efficient exchange of knowledge and expertise, and ensuring the successful realization of machine learning initiatives.

Develop and maintain project work plans, including critical tasks, milestones, timelines, interdependencies, and contingencies. Tracks and reports progress. Keeps stakeholders apprised of project status and implications for completion. Prepare clear, well-organized project-specific documentation, including, at a minimum, analytic methods used, key decision points and caveats, with sufficient detail to support comprehension and replication. Mentor other analysts on how to a) determine appropriate statistical analysis methods, b) leverage appropriate programing languages and tools, and c) generate and interpret statistical analysis outputs.

Share development and process knowledge with other analysts in order to assure redundancy and continuously builds a core of analytical strength within the organization.

Adheres to corporate standards for performance metrics, data collection, data integrity, query design, and reporting format to ensure high quality, meaningful analytic output.

Works closely with IT on the ongoing improvement of Mount Sinai’s integrated data warehouse, driven by strategic and business needs, and designed to ensure data and…