Machine Learning Engineer II (Applied Research & Model Development)

PathAI develops AI-powered pathology solutions aimed at improving diagnosis, treatment efficacy, and patient outcomes. The Machine Learning Engineer II will design, develop, and deploy machine learning models for research and product development while collaborating with biomedical data science, product, research, MLOps, and platform engineering teams.

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) plus 2–4 years of experience, or a PhD Machine Learning, Computer Science, Data Science, Statistics, Applied Mathematics (or a closely related discipline) with 0–2 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 contribute to experimental design, and improve ML workflows
• You have demonstrated the ability to collaborate across scientific and engineering teams
• You have the ability to work independently
• 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