Principal Machine Learning Engineer

at  apree health

ABOUT US:

At apree health we’re building an integrated health network that combines data-driven personalization, coordinated care delivery, and a best-in-class health navigation platform. This combination provides a vastly better health and care experience for our members while simultaneously lowering the total cost of care for our population. To date, we have partnered with more than 240 large enterprise customers, spanning millions of lives, to improve healthcare outcomes.

ABOUT THE ROLE:

Are you passionate about leveraging machine learning to revolutionize healthcare and address the affordability crisis? Do you regularly find ways of applying AI to solve business needs and know how to prioritize objectives in terms of ROI? Do you enjoy working with others across the business who are interested in AI?
As a Principal Machine Learning Engineer, you’ll play a pivotal role in developing and deploying AI models that drive actionable insights, enhance patient care, and optimize healthcare outcomes. The primary focus of this role is to personalize the experience to identify the best care for each member. In this role you will also work cross-functionally with engineers, data scientists, analysts, product managers, designers, and business leaders throughout the organization.

WHAT YOU’LL DO:

• Architect the design, development, and deployment of scalable machine learning models to extract valuable insights from complex healthcare data that facilitate decision-making and drive innovation in healthcare delivery.
• Utilize your deep understanding of machine learning and statistical methods to mentor junior data scientists, analysts, and engineers.
• Collaborate closely with cross-functional teams to integrate data from various sources, including electronic health records, medical claims, and wearable devices.
• Champion best practices in machine learning engineering, including model evaluation, monitoring, and maintenance, to ensure robustness and reliability in production environments.
• Drive the adoption of Google Cloud Platform (GCP) services, particularly Vertex AI, to streamline model development, training, deployment, and monitoring processes.
• Stay abreast of the latest advancements in machine learning, healthcare technology, and cloud computing to continuously enhance our analytics capabilities.