Senior Machine Learning (ML) Engineer (CCC Casualty / Claims Intelligence)

Role overview Own machine learning models and evaluation from initial analysis through production, using evidence to guide product decisions in auto injury claims. The work spans statistical methods and large language model features for medical bill processing, claims decision support, and rules-based or agentic tools used by claims professionals.

Responsibilities - Build and deploy statistical, machine learning, and hybrid language model solutions using claims data, including retrieval and embeddings. - Create evaluation datasets with labelers and subject matter experts, then run ongoing assessments as products change. - Compare model outputs with expert decisions and investigate errors to understand where systems work or fail. - Design experiments, establish baselines, and analyze customer impact and return on investment. - Explain findings to product, sales, and customer audiences so results can inform decisions.

Requirements - Typically five or more years in machine learning, data science, or quantitative engineering. - Strong grounding in statistics, probability, and experiment design, gained through education, research, or equivalent experience. - Strong Python and SQL skills, with experience putting models into production and measuring their performance. - Practical experience with both statistical machine learning and language model approaches, including retrieval-augmented generation, embeddings, vector search, and output evaluation. - Experience using AI-assisted tools to work more efficiently, with examples of how you apply them.

Nice to have - Applied causal inference, survival analysis, or calibration methods for business decisions. - Experience fine-tuning models for specialized tasks.

Benefits and work setup - Listed base salary range is $180,000–$225,000, with bonus eligibility. - Benefits include health coverage, paid time off, retirement matching, tuition reimbursement, wellness programs, and stock purchase options.