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Staff Software Engineer – AI/ML

Staff Software Engineer – AI/ML

CompanyNatera
LocationSan Carlos, CA, USA
Salary$136300 – $195350
TypeFull-Time
DegreesMaster’s, PhD
Experience LevelSenior

Requirements

  • 5+ years of experience in AI/ML engineering with applied projects in healthcare, RCM, or medical billing
  • Strong proficiency in Python, SQL, and ML libraries (scikit-learn, XGBoost, TensorFlow/PyTorch, etc.)
  • Experience with OCR/NLP tools such as Tesseract, AWS Textract, spaCy, or similar
  • Proven track record building ML pipelines that integrate with backend systems or RPA tools
  • Deep understanding of revenue cycle metrics: A/R aging, denial codes, CPT/HCPCS/ICD-10, claim statuses
  • Experience working with EHR, clearinghouse, or payer data (e.g., 837/835 formats, ERA/EOBs)
  • Strong problem-solving and communication skills with a product and outcome-driven mindset
  • Understanding of HIPAA and data privacy/security best practices for handling PHI

Responsibilities

  • Develop and deploy AI/ML models for denial prediction, claim prioritization, and payer behavior analysis
  • Use NLP and computer vision (OCR) to extract structured data from unstructured inputs (e.g., paper faxes, remittance files, EOBs)
  • Build automated pipelines to monitor open accounts receivable (A/R) and generate exception reports
  • Support optimization of CPT/ICD-10 coding accuracy using ML classifiers and claim outcome modeling
  • Collaborate with Billing and RCM teams to identify gaps in collections, trends in denials, and areas for automation
  • Create dashboards and tools to support reimbursement forecasting, financial performance reporting, and compliance audits
  • Work with Compliance and Privacy teams to ensure HIPAA-compliant handling of PHI in all data pipelines
  • Contribute to ongoing automation efforts to improve workflow efficiency across the billing cycle

Preferred Qualifications

  • Experience working with medical billing platforms (Waystar, eClinicalWorks, Epic, Cerner, etc.)
  • Familiarity with financial forecasting, bad debt analysis, and payer reimbursement models
  • Background in bioinformatics, digital health, or clinical operations is a plus
  • M.S. or Ph.D. in Computer Science, Data Science, Biomedical Informatics, or related field