Senior Machine Learning Engineer – CCC Casualty, Claims Intelligence

Job not on LinkedIn

🔥 12 hours ago

🌽 Illinois – Remote

🌽 Illinois – Remote

💵 $180k - $225k / year

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

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👻 Ghost score 6%

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EvolutionIQ

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🏥 Healthcare

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EvolutionIQ is a cutting-edge technology company specializing in AI-powered claims guidance to improve the efficiency of insurance claims processing. The company focuses on simplifying complex claims data into actionable insights, enabling claims professionals to provide higher quality service with less effort and more personalized support. EvolutionIQ's solutions are specifically designed to address challenges in areas such as Group & Individual Disability, Workers' Compensation, and Income Protection, enhancing claimant experience, reducing costs, and optimizing process efficiency. The company prides itself on harnessing human-centric AI to drive better outcomes in claims management.

📋 Description

• 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

• 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

• 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

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