Applied Machine Learning Engineer (All Levels)

Allstate Technology Solutions is seeking an Applied Machine Learning Engineer (Remote) to design, build, and operate models across the full lifecycle to deliver real business impact.

Responsibilities

• Assist with model development, data exploration, validation, and deployment, collaborating through pair programming and adopting best practices.
• Develop and deploy production grade ML models, own key components of ML projects, and partner with cross functional teams.
• Drive end to end ML initiatives, design and orchestrate ML pipelines, coach junior engineers, and help shape technical direction.

Requirements

• Entry Level: 0–2 years of academic, internship, or professional experience
• Mid Level: 3+ years building ML solutions
• Senior Level: 3+ years deploying and operating ML systems
• Bachelor’s degree, STEM preferred
• Proficiency in Python with pandas, numpy, and scikit-learn, plus solid software engineering fundamentals
• Experience with ML libraries such as scikit-learn, XGBoost, and LightGBM
• Experience with PyTorch or TensorFlow
• SQL for data exploration and feature engineering
• Knowledge of model evaluation and interpretability methods, for example 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 experience
• Familiarity with APIs, containers, CI/CD, monitoring, drift detection
• Experience with 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