IT Software Engineer 3

Cullerton Group has a new opportunity for an IT Software Engineer 3 / Senior MLOps Software Engineer. The work will be done in a hybrid onsite environment in Chicago, IL, with 2–3 days onsite per week. This is a long-term position with an initial duration of 12 months and strong potential for extension. Compensation is up to $74.8/hr full benefits (vision, dental, health insurance, 401k, and holiday pay).

Job Summary

This role supports the design, development, and operation of a modern MLOps platform that enables teams to build, deploy, and maintain production-grade machine learning models at scale. The engineer will focus on creating self-service ML development tooling, scalable cloud-based pipelines, and reliable operational frameworks that support the full lifecycle of AI and machine learning solutions. The position works closely with data science, engineering, and platform teams to enable data-driven decision-making across the enterprise.

• Key ResponsibilitiesDesign and implement scalable, secure architectures and pipelines for building, deploying, and monitoring production machine learning applications
• Build and enhance MLOps platforms and self-service ML development tools to support model training, deployment, and lifecycle management
• Develop cloud-based MLOps solutions and pipelines using platforms such as AWS
• Implement CI/CD workflows, containerization, versioning, monitoring, and automation for machine learning systems
• Collaborate with internal stakeholders to define requirements, create user stories, and deliver platform capabilities that improve developer productivity
• Required QualificationsBachelor’s degree with 5 years of experience, or Master’s degree with 3 years of experience, in Computer Science, Engineering, or a related field
• 5 years of experience with object-oriented programming languages such as Python, Java, Go, or C/C
• Hands-on experience with MLOps frameworks (e.g., MLflow, Kubeflow)
• Strong experience with cloud-based solutions and building MLOps pipelines (AWS preferred)
• Proficiency with DevOps tools and practices, including CI/CD, Git/GitHub, and containerization using Docker and Kubernetes
• Preferred QualificationsExperience building model inference systems and advanced deployment methods integrated with MLOps components
• Knowledge of Kubernetes deployment tooling such as Helm and Helmfile
• Experience with infrastructure orchestration tools such as Terraform or CloudFormation
• Exposure to observability and model monitoring tools for performance, data drift, or concept drift

Why This Role?

This position offers the opportunity to work on impactful, enterprise-scale AI and machine learning platforms that enable advanced analytics and data-driven decision-making. Cullerton Group provides a professional consulting environment with strong partnerships, meaningful technical challenges, and opportunities to grow within modern cloud and MLOps ecosystems.