Machine Learning Engineer II/III (Applied Research & Model Development)

PathAI•Boston, MA

13h•$107,250 - $200,100

About The Position

PathAI's mission is to improve patient outcomes with AI-powered pathology. Our platform promises substantial improvements to the accuracy of diagnosis and the efficacy of treatment of diseases like cancer, leveraging modern approaches in machine learning and artificial intelligence. We have a track record of success in deploying AI algorithms for histopathology in translational research, pathology labs and clinical trials. Rigorous science and careful analysis is critical to the success of everything we do. Our team, composed of diverse employees with a wide range of backgrounds and experiences, is passionate about solving challenging problems and making a huge impact on patient outcomes. We are seeking Machine Learning Engineers (Applied Research & Model Development) to join our team and tackle unique machine learning challenges to advance medicine and improve patient care. You will work closely with teams across biomedical data science, product development, translational research, MLOps, and platform engineering to develop and deploy machine learning models for our AI products and services.

Requirements

Master’s degree plus 2–4 years of experience, or Ph.D. with 0–2 years of experience (MLE II).
Proven track record of developing and deploying machine learning models into production or research applications (MLE II).
Strong proficiency in Python, ML frameworks, and data pipeline development (MLE II).
Demonstrated ability to work independently on projects, contribute to experimental design, and improve ML workflows (MLE II).
Strong communication skills and ability to collaborate across scientific and engineering teams (MLE II).
Master’s degree plus 5+ years of experience, or Ph.D. with 3+ years of experience (MLE III).
Deep expertise in ML, computer vision, or biomedical AI, with a history of high-impact contributions (publications, open-source, or products) (MLE III).
Mastery of ML frameworks, software engineering best practices, and deployment pipelines (MLE III).
Ability to lead end-to-end projects, mentor others, and set technical direction (MLE III).
Experience articulating technical improvements into business or clinical impact (MLE III).
Strong record of contributions to scientific strategy (abstracts, manuscripts, conference presentations) (MLE III).

Nice To Haves

Team players, willing to do the work no matter how big or small it may be, and who are passionate about everything they do.

Responsibilities

Design, develop, and deploy machine learning models for research and product development projects.
Collaborate cross-functionally with scientists, engineers, and product teams to translate biological and clinical requirements into scalable ML solutions.
Contribute to experimental design and analysis, including ideation, documentation, and reporting.
Participate in knowledge sharing and team initiatives (e.g., design reviews, journal clubs, ML best practices, governance activities).
Improve ML pipelines and infrastructure in partnership with MLOps and platform teams.
Publish and present scientific work, supporting abstracts, manuscripts, and conference contributions.
Contribute to projects with guidance, implement models, and learn best practices (MLE I).
Independently deliver on projects, improve processes, and mentor junior engineers (MLE II).
Lead initiatives end-to-end, set technical direction, and identify new opportunities with clear business and scientific impact (MLE III).