Machine Learning Engineer

Machine Learning Engineer

📍 Hybrid – San Francisco Bay Area, CA

💰 $170,000 – $220,000 + Equity

About the Role

We're looking for a Machine Learning Engineer to design, build, and deploy ML solutions that support healthcare operations and improve patient experiences. You'll work on predictive models, NLP applications, LLM-powered features, and the scalable AI infrastructure that supports them — partnering closely with Product, Engineering, Data Science, and business stakeholders to bring AI-driven products to market.

This is a chance to join a rapidly growing HealthTech company using AI and machine learning to modernize healthcare delivery at scale, and to build solutions that help healthcare organizations make smarter decisions and deliver better outcomes for patients.

What You'll Do

• Design, build, and deploy machine learning solutions across predictive modeling, NLP, and generative AI/LLM-powered features
• Work with large-scale healthcare datasets, including clinical information, patient engagement data, and operational workflows
• Develop and maintain MLOps pipelines for model training, deployment, monitoring, and evaluation
• Collaborate cross-functionally with Product, Engineering, Data Science, and business teams to ship AI-driven products

Tech Stack

Python, PyTorch, AWS, Databricks, SQL, Docker, and modern machine learning frameworks

What We're Looking For

• 3–7+ years of experience building production machine learning systems, with strong software engineering fundamentals
• Experience with MLOps practices (training, deployment, monitoring, evaluation)
• Preferred: background in Healthcare, HealthTech, or Life Sciences, and/or experience with NLP, recommendation systems, predictive analytics, or Generative AI
• Comfort working in a fast-paced, collaborative environment and solving complex, ambiguous problems

Compensation & Benefits

Competitive base salary ($170,000–$220,000), equity, comprehensive benefits, and flexible working arrangements.