✦ Luna Orbit — AI & Machine Learning

Applied Machine Learning Engineer (All Levels)

at Allstate

📍 USA - IL (Remote) Remote Posted March 06, 2026
Type Full-Time
Experience mid
Exp. Years 3+ years
Education Bachelor's degree (STEM preferred).
Category AI & Machine Learning

Allstate is seeking an Applied Machine Learning Engineer to design, build, and operate ML models that create business impact. The role involves full ML lifecycle management, collaboration, and deployment.

  • Support model development and deployment
  • Build and deploy ML models
  • Lead ML initiatives and pipelines
  • Mentor junior engineers
  • Collaborate with cross-functional teams

The role involves working with Python, ML libraries like scikit-learn, XGBoost, LightGBM, PyTorch, TensorFlow, and tools like Terraform and SQL to develop, deploy, and monitor machine learning models.

The ideal candidate is an experienced machine learning engineer with 3+ years of experience in building and deploying ML models using Python and libraries like XGBoost and LightGBM. They should have strong collaboration skills, mentoring experience, and familiarity with ML pipelines and deployment processes.

Pythonscikit-learnXGBoostLightGBMSQL
PyTorchTensorFlowTerraformJavaTypeScript
scikit-learnXGBoostLightGBMPyTorchTensorFlowTerraformSQL
Pythonscikit-learnXGBoostLightGBMPyTorchTensorFlowSQLSHAPTerraformJavaTypeScript
PythonPython (Programming Language)scikit-learnXGBoostLightGBMPyTorchTensorFlowSQLSHAPTerraformJavaTypeScript
CommunicationCollaborationLeadershipMentoringProblem-solving
Industry Insurance
Job Function Design, develop, and operationalize machine learning models to solve business problems
Machine Learning EngineerPythonscikit-learnXGBoostLightGBMPyTorchTensorFlowSQLSHAPTerraformJavaTypeScriptML lifecycleModel deploymentModel monitoringData explorationFeature engineeringML pipelinesMentoringLeadership

Lack of experience with Python or ML libraries, No experience with ML deployment or pipelines, Unwillingness to work remotely, Less than 3 years of relevant ML experience

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