Applied Machine Learning Engineer (All Levels)

Allstate Technology Solutions is seeking an Applied Machine Learning Engineer at all levels for a fully remote position. The role centers on designing, building, and operating machine learning models across the full lifecycle to deliver tangible business impact. Location is remote, with a salary range of USD 110,000 to 181,025 per year, and a bachelor’s degree in a STEM field is preferred.

Responsibilities

• Assist with model development, data exploration, testing, and deployment activities; collaborate through pair programming and adoption of best practices.
• Build and deploy production ML models, own key components of ML projects, and partner with cross functional teams.
• Lead end-to-end ML initiatives, architect ML pipelines, mentor junior engineers, and influence the technical direction of projects.

Requirements

• 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
• Bachelor’s degree; STEM fields preferred
• Python (pandas, numpy, scikit-learn) and strong software engineering foundations
• ML libraries such as scikit-learn, XGBoost, LightGBM
• PyTorch or TensorFlow
• SQL for data exploration and feature engineering
• Knowledge of model evaluation and interpretability with SHAP
• Willingness to learn Terraform, Java, and TypeScript; no prior experience required

Technologies

• Python, pandas, numpy, scikit-learn
• XGBoost, LightGBM
• PyTorch, TensorFlow
• SQL
• SHAP
• Terraform, Java, TypeScript
• Spark
• Docker
• MLflow
• SageMaker, Azure ML
• AWS, Azure, GCP

Benefits

• Comprehensive technology setup including laptop, monitors, headset, keyboard, and mouse
• Monthly connectivity reimbursement for remote workers

Soft Skills

• Strong communication and collaboration abilities
• Ability to work with technical and non-technical partners
• Leadership and mentoring experience for senior roles

Preferred Qualifications

• 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, natural language processing, computer vision, or LLM/RAG
• Prior ownership of end-to-end ML products
• Insurance or financial services experience