Staff Machine Learning Engineer

About the role

As a Staff ML Engineer, you will design, develop, and optimize AI systems including ML pipelines, document understanding models, and LLM-powered workflows to automate complex credentialing and provider verification processes. You'll identify high-leverage opportunities and deliver intelligent, scalable solutions that reduce administrative burden across the healthcare system. Expect to work with full autonomy, affect the company roadmap, and ship features that make a meaningful impact. All on a supportive and experienced team of engineers, PMs, and designers.

This role reports to one of our Engineering Managers and base compensation for this role may land between $190,000–$240,000. In addition to base salary, Medallion offers equity and benefits as part of the total compensation package. Many factors are considered when determining pay including: market data, geographic location, skills, qualifications, experience, and level.

What you'll do

• Scope and lead ML initiatives end-to-end from identifying opportunities and defining the problem through production deployment and iteration
• Design, develop, and optimize ML models and AI systems for document parsing, extraction, classification, and intelligent automation
• 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
• Help develop our AI roadmap, balancing key technical and product tradeoffs
• Drive architectural decisions for ML systems and establish best practices for development, evaluation, and deployment
• Teach and mentor members of the engineering team, constantly modeling how great ML software should be developed

Requirements

• 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