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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Mid Level AI/ML Engineer/Chicago OR Detroit Local - **Company:** Kelly Services Inc. - **Location:** Chicago, IL, United States - **Experience:** Experienced - **Salary:** $100,000.0 - $120,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Cloud Computing, Continuous Integration, Information Engineering, DevOps, Monitoring of Systems, Python (Programming Language), Machine Learning, SQL Databases, Management of Software Versions, Cloud Platform System, Delivery Pipeline, Large Language Models, Containerization, AI Platforms, Kubernetes, Information Technology, Low Latency, Data Analytics, Machine Learning Operations, Software Version Control, Docker, Databricks - **Published:** August 28, 2026 - **Apply:** https://dejobs.org/x/x/B1C1AD6FEEDC45BD8294E08FD9EC08B1/job/ ## About the Role * Bachelor's degree in Computer Science, Engineering, or a related field, or comparable experience * 3-5 years of experience in DevOps, MLOps, data engineering, or a related infrastructure/operations role * Hands-on experience deploying machine learning models into production environments * Working knowledge of Databricks and cloud AI platforms (AWS preferred, including familiarity with services like Bedrock) * Experience with containerization and orchestration tools (Docker, Kubernetes or equivalent) * Proficiency in Python and familiarity with CI/CD tooling * Experience with monitoring and observability tooling for production systems * Solid understanding of data analytics fundamentals Desired Skills & Experience * Familiarity with LLM deployment considerations (latency, cost, versioning) * Experience with SQL ## Description Our client is a global performance marketing organization operating at the intersection of brand marketing, technology, and analytics, helping businesses design and manage data-driven marketing and brand strategies. They are hiring for a Mid-Level AI/ML Ops Engineer to build and maintain the infrastructure, deployment pipelines, monitoring, and cloud systems that gets AI and machine learning models into production reliably, securely, and at scale. This is a hands-on opportunity to own the operational backbone of a growing AI practice, working side by side with AI Engineers and the AI Tech Lead rather than setting architecture in isolation. You will take deployment and infrastructure requirements and turn them into dependable, monitored production systems, all while deepening your expertise across MLOps, cloud AI platforms, and LLM deployment. It is a great fit for someone who is detail oriented and reliability focused, stays calm and methodical when production issues come up, and wants room to grow into a stronger voice on the operational side of AI/ML., * Databricks and AWS cloud AI platforms, including Bedrock * Docker and Kubernetes (or equivalent orchestration) * Python and CI/CD tooling * Monitoring and observability platforms Daily Responsibilities * Build and maintain CI/CD pipelines for deploying AI/ML models into production * Implement monitoring and observability to catch performance degradation, drift, and failures early * Manage cloud infrastructure supporting AI workloads, including containerized services and cloud AI platforms * Collaborate with AI Engineers and the AI Tech Lead to translate requirements into deployment plans * Troubleshoot production issues and support model versioning, reproducibility, and rollback processes * Monitor and optimize the cost and resource efficiency of AI/ML workloads, flagging operational risks before they become incidents The Offer * Bonus eligible You will receive the following benefits: * Medical, Dental, and Vision Insurance * Vacation Time * Stock Options ## Related Videos - [DevOps for AI: running LLMs in production with Kubernetes and KubeFlow](https://www.wearedevelopers.com/videos/1222-devops-for-ai-running-llms-in-production-with-kubernetes-and-kubeflow) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Supercharge your cloud-native applications with Generative AI](https://www.wearedevelopers.com/videos/950-supercharge-your-cloud-native-applications-with-generative-ai) - [OLTP in the Lakehouse: Redefining Data for AI Workloads](https://www.wearedevelopers.com/videos/2038-oltp-in-the-lakehouse-redefining-data-for-ai-workloads) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)