Senior Machine Learning Engineer – Casualty, Claims Intelligence

CCC Intelligent Solutions

. Own models and evaluations end to end within a problem area and turn results into product decisions .

Posted 11/3/2026full-timeRemote • Illinois • United StatesSenior💰 $180,000 - $225,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying machine learning models, with a strong foundation in statistics and experiment design. Capable of translating complex data insights into actionable product decisions while effectively communicating results to diverse stakeholders.

Highest-signal resume keywords

Machine LearningStatistical AnalysisPython ProgrammingSQL ProficiencyModel Deployment

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Statistical MLLLM-Based ApproachesExperiment DesignCausal InferenceSurvival AnalysisCalibration MethodsData EvaluationQuantitative EngineeringData ScienceModel Fine-Tuning

Soft Skills

Clear CommunicationCollaboration

Tools & Technologies

AI-Assisted ToolsClaims Decision SupportAgentic Rules Platform

Industry Keywords

Auto Casualty ClaimsInjury ClaimsReal Claims DataGold DatasetsROI Analysis

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Own models and evaluations end to end within a problem area and turn results into product decisions
Build and ship statistical, ML, and hybrid LLM models, including retrieval and embeddings, on real claims data
Design evaluations and gold datasets with data labelers and subject matter experts
Run evaluations continuously as the product changes
Measure impact through experiment design, baselines, and ROI analysis
Explain results clearly to product, sales, and customers
Build AI-native products for auto casualty and injury claims, including medical bills, claims decision support, and the Agentic Rules Platform
Ship models or evaluations to production

Requirements

What you’ll need

Typically 5+ years of experience in machine learning, data science, or quantitative engineering roles
A strong quantitative foundation (statistics, probability, experiment design) from a degree, research, or equivalent experience
Strong Python and SQL
Track record of taking models to production and measuring how they perform
Hands-on experience with statistical ML and LLM-based approaches (RAG, embeddings, vector search), including evaluating LLM outputs
Real experience working faster with AI-assisted tools, with examples you can walk us through
Video interview required
Candidates are not permitted to use generative AI or automated assistance during interviews unless explicitly allowed
Nice to have: causal inference, survival analysis, or calibration methods applied to business decisions
Nice to have: experience fine-tuning models for domain-specific tasks

Benefits

Comp & perks

401K Match
Paid time off
Annual Incentive Plan Performance Bonus
Comprehensive health insurance
Adoption Assistance
Tuition Reimbursement
Wellness Programs
Stock Purchase Plan options
Employee Resource Groups