Senior Machine Learning Engineer – CCC Casualty, Claims Intelligence

EvolutionIQ

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

Posted 11/4/2026full-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 evaluating AI-native products, particularly in the auto casualty business, with a strong focus on machine learning, statistical analysis, and model deployment. Capable of translating complex data insights into actionable product decisions and 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

Machine LearningStatistical AnalysisExperiment DesignCausal InferenceSurvival AnalysisModel Fine-TuningLLM-Based ApproachesEmbeddingsVector SearchROI Analysis

Soft Skills

Clear CommunicationCollaboration

Tools & Technologies

AI-Assisted ToolsData Labeling Tools

Industry Keywords

Auto ClaimsInjury SideQuantitative EngineeringReal Claims DataGold Datasets

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 AI-native products for CCC's auto casualty business, focused on the injury side of auto claims
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, and run them continuously as the product changes
Measure impact through experiment design, baselines, and ROI analysis
Explain results clearly to product, sales, and customers
Run an evaluation on real data during the first month
Ship a model or evaluation to production within six months and support evidence-based product decisions

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, and a track record of taking models to production and measuring how they perform
Hands-on experience with both 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
Causal inference, survival analysis, or calibration methods applied to business decisions
Experience fine-tuning models for domain-specific tasks
A video interview is required for this position
Candidates are not permitted to use generative AI or automated assistance during interviews unless explicitly allowed by the interview team for a specific exercise

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