Applied Machine Learning Engineer (All Levels) (Illinois)
At Allstate, great things happen when our people work together to protect families and their belongings from life’s uncertainties. And for more than 90 years, our innovative drive has kept us a step ahead of our customers’ evolving needs. From advocating for seat belts, air bags and graduated driving laws, to being an industry leader in pricing sophistication, telematics, and, more recently, device and identity protection.
Job Description
Join Allstate Technology Solutions, a pioneering force committed to revolutionizing the way our employees, agencies, and customers interact digitally. Our mission is to harness cutting-edge technology, innovative product design, and the power of artificial intelligence to create a world‑class customer experience. We aim to redefine the customer experience, ensuring consistency and operational efficiency across all touchpoints and channels.Become a part of our story.
At Allstate Technology Solutions, you’ll find a collaborative and dynamic team focused on exploring new capabilities and pushing the boundaries of what’s possible. The team works in a continuous innovation cycle of ideas, research, testing, analysis, and delivery. About the Role
As a Machine Learning Engineer at Allstate, you will design, build, and operate machine-learning models that deliver real business impact. You’ll work across the full ML lifecycle—including data exploration, feature engineering, model building, deployment, monitoring, and ongoing improvement. Our team emphasizes pair programming and test-driven development to ensure high-quality, reliable solutions. What You’ll Do (Responsibilities Vary by Level) 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.
Education
Bachelor’s degree (STEM preferred).
Experience
• 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.
Technical Skills
• Python (pandas, numpy , scikit-learn) and software engineering foundations.
• ML libraries:
-Experience with libraries such as s cikit-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 ).
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, NLP, computer vision, or LLM/RAG.
• Prior ownership of end-to-end ML products.
• Insurance or financial services experience.
#LI-PG1
Skills
Applied Machine Learning, Machine Learning (ML), Machine Learning Algorithms, Model Building, Model Development, Model Evaluation, Python (Programming Language), PyTorch, Structured Query Language (SQL), TensorflowCompensation
Compensation offered for this role is 110,000.00 - 181,025.00 annually and is based on experience and qualifications.The candidate(s) offered this position will be required to submit to a background investigation.
Joining our team isn’t just a job — it’s an opportunity. One that takes your skills and pushes them to the next level. One that encourages you to challenge the status quo. One where you can shape the future of protection while supporting causes that mean the most to you. Joining our team means being part of something bigger – a winning team making a meaningful impact.
Allstate generally does not sponsor individuals for employment-based visas for this position.
Effective July 1, 2014, under Indiana House Enrolled Act (HEA) 1242, it is against public policy of the State of Indiana and a discriminatory practice for an employer to discriminate against a prospective employee on the basis of status as a veteran by refusing to employ an applicant on the basis that they are a veteran of the armed forces of the United States, a member of the Indiana National Guard or a member of a reserve component.
For jobs in San Francisco, please click “ here ” for information regarding the San Francisco Fair Chance Ordinance.
For jobs in Los Angeles, please click “ here ” for information regarding the Los Angeles Fair Chance Initiative for Hiring Ordinance.
To view the “EEO Know Your Rights” poster click “ here ”. This poster provides information concerning the laws and procedures for filing complaints of violations of the laws with the Office of Federal Contract Compliance Programs.
To view the FMLA poster, click “ here ”. This poster summarizing the major provisions of the Family and Medical Leave Act (FMLA) and telling employees how to file a complaint.
It is the Company’s policy to employ the best qualified individuals available for all jobs. Therefore, any discriminatory action taken on account of an employee’s ancestry, age, color, disability, genetic information, gender, gender identity, gender expression, sexual and reproductive health decision, marital status, medical condition, military or veteran status, national origin, race (include traits historically associated with race, including, but not limited to, hair texture and protective hairstyles), religion (including religious dress), sex, or sexual orientation that adversely affects an employee's terms or conditions of employment is prohibited. This policy applies to all aspects of the employment relationship, including, but not limited to, hiring, training, salary administration, promotion, job assignment, benefits, discipline, and separation of employment.
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