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

PathAI’s mission is to improve patient outcomes with AI-powered pathology. Our platform leverages modern machine learning and artificial intelligence to enhance the accuracy of diagnosis and the efficacy of treatment for diseases like cancer. We deploy AI algorithms for histopathology in translational research, pathology labs, and clinical trials, backed by rigorous science and careful analysis. Our diverse team is passionate about solving challenging problems and making a significant impact on patient care.

About the role

We are seeking Machine Learning Engineers (Applied Research & Model Development) to tackle unique machine learning challenges that advance medicine and improve patient care. You will collaborate 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.

You will work in a company where all employees prioritize patient outcomes, and every contribution—no matter the size—supports our mission to pioneer better patient care. You’ll collaborate with leading innovators in AI and medicine, playing a critical role in product development to directly impact patient outcomes.

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.

Level-specific Expectations

• MLE I: Contribute to projects with guidance, implement models, and learn best practices.
• MLE II: Independently deliver on projects, improve processes, and mentor junior engineers.
• MLE III: Lead initiatives end-to-end, set technical direction, and identify new opportunities with clear business and scientific impact.

Requirements

We welcome applicants across all MLE levels. Minimum qualifications differ by level:

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

Pay

Individual compensation packages are tailored based on skills, experience, qualifications, and other job-related factors.

• Machine Learning Engineer II: $107,250 - $164,450 annual pay range.
• Machine Learning Engineer III: $130,500 - $200,100 annual pay range.

Not overtime eligible.