Staff Machine Learning Engineer

About Medallion

At Medallion, we believe healthcare teams should focus on what truly matters—delivering exceptional patient care. That’s why we’ve built a leading provider operations platform to eliminate the administrative bottlenecks that slow healthcare organizations down. By automating licensing, credentialing, payer enrollment, and compliance monitoring, Medallion empowers healthcare operations teams to streamline their workflows, improve provider satisfaction, and accelerate revenue generation, all while ensuring superior patient outcomes.

As one of the fastest-growing healthcare technology companies—ranked No. 3 on Inc. Magazine’s 2024 Fastest-Growing Private Companies in the Pacific Region, No. 5 on LinkedIn's 2024 Top Startups in the US, a Glassdoor Best Place to Work in 2024 & 2025, and featured on The Today Show—Medallion is revolutionizing provider network management. Our CEO, Derek Lo, has been named one of the Top 50 Healthcare Technology CEOs of 2024 by The Healthcare Technology Report. Backed by $130M in funding from world-class investors like Sequoia Capital, Google Ventures, Optum Ventures, Salesforce Ventures, Acrew Capital, Washington Harbour, and NFDG, we’re on a mission to transform healthcare at scale.

We prioritize candidate safety. Please be aware that official communication will only come from @medallion.co email addresses.

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 environment
• Care deeply about both technical success and product success
• Excellent communication skills

You might also have:

• Experience with healthcare data, compliance workflows, or regulated industries
• Background in document understanding, OCR/ICR, or information extraction from unstructured data
• Hands-on experience with MLOps tooling (MLflow, W&B, Airflow) or cloud ML infrastructure (SageMaker, Vertex AI, Bedrock)
• Graduate work in a quantitative field (CS, statistics, ML, or related)

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