IT Software Engineer

Senior MLOps Software Engineer

Location:

Chicago, IL (Hybrid)

Job Type: W2 Contract

Schedule:

Monday - Friday, 8:30am-4:30pm CST

Pay Rate: $70-75/hourly with optional benefits packages including PTO, medical insurance, and 401k

The MLOps Platform Team works within the Enterprise Data and Analytics Organization at Caterpillar, driving the ability to support the full life-cycle of AI and machine learning development through to beyond production. The team helps build a platform that enables data‑driven decisions across the enterprise, assists teams in building high‑value data and AI/ML products, and supports the operationalization and reliability of all models.

We are searching for a driven, highly skilled MLOps Engineer to join our MLOps Platform team  role involves building the MLOps Platform, creating self‑service ML development tooling, and fostering platform adoption. You should have ideas on how to create a great user experience for those building, deploying, and operationalizing production‑quality machine learning models.

• Define scalable and secure architectures, frameworks, and pipelines for building, deploying, and diagnosing production ML applications
• Enable users & teams on the ML platform; troubleshoot and debug user issues; maintain user‑friendly documentation and training
• Collaborate with internal stakeholders to build a comprehensive MLOps Platform
• Design and implement cloud solutions and build MLOps pipelines on cloud solutions (e.g., AWS)
• Develop standards and examples to accelerate the productivity of data science teams
• Run code refactoring and optimization, containerization, deployment, versioning, and monitoring of its quality, including data & concept drift
• Create ways to automate the testing, validation, and deployment of data science models
• Provide best practices and execute POC for automated and efficient MLOps at scale

• Bachelor's degree with 5+ years experience
• Master's degree with 3+ years experience

• 5+ years of experience working with an object‑oriented programming language (Python, Golang, Java, C/C++ etc.)
• Experience with MLOps frameworks like MLflow, Kubeflow, etc.
• Proficiency in programming (Python, R, SQL)
• Ability to design and implement cloud solutions and build MLOps pipelines on cloud solutions (e.g., AWS)
• Strong understanding of Dev Ops principles and practices, CI/CD, etc. and tools (Git, Git Hub, jFrog Artifactory, Azure Dev Ops, etc.)
• Experience with containerization technologies like Docker and Kubernetes
• Strong communication and collaboration skills
  
  Ability to help work with a team to create User Stories and Tasks from higher‑level requirements

• Ability to create model inference systems with advanced deployment methods that integrate with other MLOps components like MLflow
• Knowledge of inference systems like Seldon, Kubeflow, etc.
• Knowledge of deploying applications and systems in Langfuse or Kubernetes using Helm and Helmfile
• Knowledge of infrastructure orchestration using Clod Formation or Terraform
• Exposure to observability tools (such as Evidently AI)

• Someone who takes the initiative on their own
• Someone who does not need to be micromanaged