6 hours ago
Base Salary
$131k - $200k/yr
Responsibilities
- Design, develop, and deploy machine learning models for research and product development.
- Translate biological and clinical requirements into scalable ML solutions with scientists, engineers, and product teams.
- Contribute to experimental design, documentation, analysis, and reporting.
- Improve ML pipelines and infrastructure with MLOps and platform teams.
- Publish and present scientific work through abstracts, manuscripts, and conference contributions.
- Participate in design reviews, journal clubs, ML best-practice initiatives, and governance activities.
Requirements
- Master’s degree in Machine Learning, Computer Science, Data Science, Statistics, Applied Mathematics, or a closely related discipline plus 5 or more years of experience, or a PhD in one of these fields plus 3 or more years of experience.
- Proven experience developing and deploying machine learning models in production or research applications.
- High proficiency in Python, machine learning frameworks, and data pipeline development.
- Ability to work independently and lead or contribute to experimental design and ML workflow improvements.
- Ability to collaborate across scientific and engineering teams.
- Strong communication and interpersonal skills, including explaining technical concepts to non-experts.
- Excellent organizational skills and ability to prioritize and manage multiple projects.
Benefits
- Position based in Boston, NYC, or remote.
- Relocation benefits are not available.
- Expected base salary range is $130,500-$200,100 for the Boston, MA primary location.
Tech Stack
Categories
About PathAI
PathAI builds AI-powered pathology software and diagnostic services for biopharma, pathology labs, and health systems to support disease detection, clinical trials, and companion diagnostics. Offerings include machine-learning models for digital histopathology and a CLIA-certified lab operation. Founded in 2016 and headquartered in Boston, it operates as part of Quest Diagnostics and focuses heavily on oncology and immunology applications.