Senior Machine Learning Engineer

Responsibilities

• Build and maintain workflows and infrastructure supporting the end-to-end ML lifecycle
• Partner with researchers to productionize models and enable faster iteration
• Design and improve data and training pipelines
• Improve data processing, annotation workflows, and ML system efficiency
• Deploy and maintain background systems for model training and inference
• Build tooling for monitoring model performance, system reliability, and operational health
• Optimize ML infrastructure for speed, reliability, and cost-efficiency
• Identify and automate bottlenecks in the ML workflow

Requirements

• Several years of experience in MLOps, ML infrastructure, data engineering, or backend/platform engineering
• Experience supporting ML systems end-to-end from deployment to monitoring
• Strong experience building and owning production data or training pipelines
• Experience working with researchers or data scientists to productionize models
• Strong software engineering fundamentals and experience building production systems
• Experience with monitoring, debugging, and improving production ML or data systems
• Track record of improving reliability, scalability, or cost efficiency in ML systems
• Ability to operate in a fast-moving startup environment

Benefits

• Competitive salary and equity
• Flexible PTO
• Medical, dental, and vision coverage
• Company off-sites

About the Company

ExaCare AI is a leading health tech company on a mission to build the AI operating system for post-acute care. Our platform turns messy, unstructured referral packets into clear clinical insights and next steps, so teams can make faster, safer placement decisions with less administrative burden.