Applied Machine Learning Engineer (All Levels)

Allstate is an insurance company focused on protecting families and their belongings through innovative technology and customer experiences. The Applied Machine Learning Engineer will design, build, deploy, operate, and improve machine-learning models across the full ML lifecycle, with responsibilities varying by level from supporting model development to leading end-to-end ML initiatives and mentoring engineers.

Responsibilities:

• Entry-Level (Consultant II): Support model development, data exploration, testing, and deployments; collaborate through pair programming and learning best practices
• Mid-Level (Senior Consultant I): Build and deploy production ML models, own key components of ML projects, and partner with cross-functional teams
• Senior-Level (Senior Consultant II): Lead end-to-end ML initiatives, architect ML pipelines, mentor junior engineers, and influence technical direction

Requirements:

• 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
• • 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)
• • Strong communication and collaboration abilities
• • Ability to work with technical and non-technical partners
• • Leadership and mentoring experience for senior roles
• -Experience with PyTorch/TensorFlow is a plus
• • Spark or distributed computing
• • Familiarity with APIs, containers, CI/CD, monitoring, drift detection
• • MLflow, SageMaker, Azure ML, Docker, CI/CD
• • AWS, Azure, or GCP cloud experience
• • Experience with deep learning, NLP, computer vision, or LLM/RAG
• • Prior ownership of end-to-end ML products
• • Insurance or financial services experience