Senior Machine Learning Engineer

Requirements: Bachelor’s degreein Computer Science, Engineering, or a related field (required).Master’s degreein a related technical field or equivalent practical experience (preferred).3+ yearsproduction ML, optimization, modern data tools, and scalable engineering practices (required).Demonstrated experience withAWSservices includingS3 , ECR, and Secrets Manager .Ability to deploy and maintain production-grade machine learning solutions using Python .Apply mathematical optimization using solvers such asGurobi .Develop and support web applications integrated withmachine learningandERP systems .Apply knowledge ofoperations researchandoptimization modeling .Use database technologies such asSnowflakeandDuckDBwithSQLfor data querying. Work with containerization tools including KubernetesandDocker .Understand machine learning concepts includingtime series forecastingandclustering .Follow software engineering best practices includingversion controlandCI/CD(for example, GitHub , GitHub Actions ).Automate workflows using orchestration tools such asAstronomerorAirflow .Build and support solutions within the Databricksplatform. Use machine learning frameworks and libraries such asPyTorchandscikit-learn .TechnologiesAWS: S3, ECR, Secrets Manager PythonGurobiSnowflake, DuckDBSQLKubernetes, DockerGitHub, GitHub Actions Astronomer, Airflow DatabricksPyTorch, scikit-learn

Benefits: Medical, dental, vision, and life insurance plans with coverage starting on day one6 free sessions each year with a licensed therapist18 paid time off (PTO) days annually for full-time employees6 company holidays per year 6% company contribution to a 401(k) Retirement Savings Plan each pay period, no employee contribution required Employee discounts Tuition reimbursement Student loan refinancing Free access to financial counseling, education, and tools Maternity support programs Nursing benefits Up to 14 weeks paid leave for birth parents Up to 4 weeks paid leave for non-birth parents Location and Work Model Chicago, IL(hybrid) Compensation Anticipated base pay range:$134,100.00 – $223,500.00(per year) Eligible for an incentive target of up to 10%based on individual and company performance objectives (terms subject to change) Not eligible for visa sponsorship

Position Details: Design and deliver scalable, production-grade solutions that enhance data-driven decision-making across the enterprise. Lead development of robust automated data pipelines, deploy advanced ML and operations research models, and create reusable tools and frameworks to accelerate experimentation and model delivery. Collaborate with cross-functional teams including planning, product management, and analytics to improve availability, efficiency, and overall business performance across operational domains.