Design, develop, and optimize AI systems including ML pipelines, document understanding models, and LLM-powered workflows to automate complex credentialing and provider verification processes
Identify high-leverage opportunities and deliver intelligent, scalable solutions that reduce administrative burden across the healthcare system
Work with full autonomy, affect the company roadmap, and ship features that make a meaningful impact
Scope and lead ML initiatives end-to-end from identifying opportunities and defining the problem through production deployment and iteration
Build and maintain production ML pipelines that are robust, observable, and scalable
Integrate and fine-tune third-party AI services (OpenAI, Amazon Textract, cloud ML APIs), managing cost, latency, and quality tradeoffs
Analyze datasets to uncover patterns, validate model performance, and generate actionable insights
Drive architectural decisions for ML systems and establish best practices for development, evaluation, and deployment
Teach and mentor members of the engineering team

8+ years of experience as a software engineer, with 4+ years focused on ML or applied AI in production environments
Track record of shipping ML systems that deliver measurable business impact
Strong proficiency in Python and the modern ML/AI stack (PyTorch, Hugging Face, scikit-learn, or similar)
Experience with LLMs in production including fine-tuning, prompt engineering, RAG, and evaluation strategies
Strong ability to work cross-functionally to help define, build, and deliver on product and tech objectives
Experience mentoring and leading teams, ideally in a startup environment
Care deeply about both technical success and product success
Excellent communication skills

Staff Machine Learning Engineer

Key skills