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

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 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

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).

Compensation

Machine Learning Engineer II: $107,250 - $164,450
Machine Learning Engineer III: $130,500 - $200,100
Not overtime eligible. Eligible for equity.