
10,000+ employees
Founded 1931
💸 Finance
💰 Post-IPO Equity on 2014-01
Insurance • Finance
Allstate is an industry leader in providing insurance solutions, focusing on home, auto, device, and identity protection. With a commitment to customer well-being, Allstate aims to instill peace of mind and financial security for its customers. The company also emphasizes community impact and sustainability through various initiatives, showcasing their dedication to social responsibility and positive change.
🔥 6 minutes ago
🌽 Illinois – Remote
💵 $110k - $181k / year
⏰ Full Time
🟡 Mid-level
🟠 Senior
🤖 Machine Learning Engineer
🦅 H1B Visa Sponsor
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10,000+ employees
Founded 1931
💸 Finance
💰 Post-IPO Equity on 2014-01
Insurance • Finance
Allstate is an industry leader in providing insurance solutions, focusing on home, auto, device, and identity protection. With a commitment to customer well-being, Allstate aims to instill peace of mind and financial security for its customers. The company also emphasizes community impact and sustainability through various initiatives, showcasing their dedication to social responsibility and positive change.
• Design, build, and operate machine-learning models that deliver real business impact. • Work across the full ML lifecycle—including data exploration, feature engineering, model building, deployment, monitoring, and ongoing improvement. • Emphasize pair programming and test-driven development to ensure high-quality, reliable solutions. • Support model development, data exploration, testing, and deployments (Entry-Level). • Build and deploy production ML models, own key components of ML projects, and partner with cross-functional teams (Mid-Level). • Lead end-to-end ML initiatives, architect ML pipelines, mentor junior engineers, and influence technical direction (Senior-Level).
• Bachelor’s degree (STEM preferred). • Entry-Level: 0–2 years (academic, internship, or professional). • Mid-Level: 3+ years building ML solutions. • Senior-Level: 3+ years deploying and operating ML systems. • Python (pandas, numpy, scikit-learn) and software engineering foundations. • Experience with libraries such as scikit-learn, XGBoost, LightGBM required. • Experience with PyTorch/TensorFlow is a plus. • SQL for data exploration and feature engineering. • Knowledge of model evaluation and interpretability (e.g., SHAP). • Willingness to learn Terraform, Java, and Typescript (no prior experience required).
• Comprehensive technology setup including laptop, monitors, headset, keyboard, and mouse. • Monthly connectivity reimbursement for internet costs when working from home.
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