Machine Learning Engineer III (Applied Research & Model Development)

PathAI is hiring a Machine Learning Engineer to develop and deploy machine learning models for research and product development. The role collaborates with biomedical data science, product, translational research, MLOps, and platform teams to advance AI products and services for pathology and patient care.

Responsibilities:

• You will design, develop, and deploy machine learning models for research and product development projects
• You will collaborate cross-functionally with scientists, engineers, and product teams to translate biological and clinical requirements into scalable ML solutions
• You will contribute to experimental design and analysis, including ideation, documentation, and reporting
• You will participate in knowledge sharing and team initiatives (e.g., design reviews, journal clubs, ML best practices, governance activities)
• You will improve ML pipelines and infrastructure in partnership with MLOps and platform teams
• You will publish and present scientific work, supporting abstracts, manuscripts, and conference contributions

Requirements:

• You have a Master's degree in Machine Learning, Computer Science, Data Science, Statistics, Applied Mathematics (or a closely related discipline) with 5 or more years of experience; or a PhD Machine Learning, Computer Science, Data Science, Statistics, Applied Mathematics (or a closely related discipline) with 3 or more years of experience
• You have a proven track record of developing and deploying machine learning models into production or research applications
• You are highly proficient in Python, ML frameworks, and data pipeline development
• You have demonstrated the ability to work independently, lead/contribute to experimental design, and improve ML workflows
• You have demonstrated the ability to collaborate across scientific and engineering teams
• You have strong interpersonal and communication skills, with the ability to explain technical concepts to non-experts and thrive in ambiguous environments
• You have excellent organizational skills and the ability to prioritize and manage multiple projects efficiently