Senior ML Engineer (Healthcare AI)

TL;DR

Senior ML Engineer (Healthcare AI): Developing novel AI applications using large-scale electronic health record (EHR) data with an accent on bridging research and production. Focus on designing multimodal learning systems and applying causal inference to improve patient outcomes.

Location: Hybrid in the Greater Seattle area; must be authorized to work in the United States

Salary: $175,000 – $200,000

Company

hirify.global is a health provider-led data platform that enables clinical research using one of the most comprehensive collections of de-identified patient data in the US.

What you will do

• Design and implement advanced ML models and systems using large-scale EHR data.
• Identify and develop novel AI use cases in healthcare that have not yet been widely explored.
• Integrate structured and unstructured clinical data, including genomics, imaging, and clinical notes.
• Prototype research ideas and evolve them into scalable, production-ready solutions.
• Collaborate with clinicians, researchers, and external stakeholders from pharma and life sciences.

Requirements

• Degree (BS, MS, or PhD) in Computer Science, Machine Learning, or a related field.
• Strong foundation in machine learning, deep learning, or applied statistics.
• Experience building and deploying ML models in real-world production settings.
• Proficiency in Python and modern ML frameworks such as PyTorch or TensorFlow.
• Must be authorized to work in the United States (no visa sponsorship available).

Nice to have

• Experience working with biomedical data (EHRs, clinical notes, genomics, imaging).
• Familiarity with LLMs, foundation models, multimodal learning, or causal inference.
• Proven track record of taking ideas from research papers to production.
• Publications or demonstrated innovation in applied ML.

Culture & Benefits

• Comprehensive medical, dental, and vision insurance plans.
• 401K retirement plan.
• Work/life autonomy via flexible work hours and flexible paid time off.
• Generous parental leave.
• Professional development and training opportunities for continuous learning.