Senior ML Ops Engineer

Myparadigm; Town of Middleton (WI); On-site; USD 140,000 - 190,000; Full time

Job summary

Myparadigm is seeking a Senior ML Ops Engineer to design, build, and maintain scalable MLOps solutions across the end-to-end ML lifecycle. You will develop automated deployment pipelines, ensure production-grade reliability, and collaborate with cross-functional teams to operationalize AI solutions.

The role emphasizes model monitoring, governance, and containerized workloads using Docker and Kubernetes, with IaC practices via Terraform. A strong background in Python and Azure ML is preferred.

Qualifications

• 4+ years of professional experience in software engineering, machine learning engineering, MLOps, platform engineering, DevOps, or related field.
• Strong understanding of the ML lifecycle: training, validation, deployment, monitoring, retraining.
• Experience building automated ML pipelines and CI/CD workflows.

Responsibilities

• Design, build, and maintain scalable MLOps solutions for end-to-end ML lifecycle.
• Develop and optimize automated ML deployment pipelines for production environments.
• Deploy and support ML models ensuring scalability, reliability, and security.
• Implement model registries, experiment tracking, versioning, and governance.

Skills

MLOps

Python

CI/CD

Docker

Kubernetes

Terraform

MLflow

Kubeflow

Azure ML

Databricks

Model monitoring

Education

Bachelor's degree in CS/DS/AI

Tools

Azure Machine Learning

Databricks

Job description

Paradigm is a software company transforming the way that the residential, construction & building product industries operate across the globe. We are looking for a Senior ML Ops Engineer to be part of revolutionizing these industries. We are building the future with modern software engineering, agent-assisted systems, and mobile-first experiences. We are powered by our parent company, Builders FirstSource (NYSE: BLDR): a Fortune 300 company with over $23 billion in revenue and more than 29,000 employees across 550+ locations, BFS is redefining construction through data, digital infrastructure, and AI-powered innovation.

What You Will Do:

• Design, build, and maintain scalable MLOps solutions that support the end-to-end machine learning lifecycle, including model training, deployment, monitoring, and retraining.
• Develop and optimize automated ML deployment pipelines, ensuring reliable, reproducible, and efficient model delivery to production environments.
• Deploy and support machine learning models and AI solutions in production, maintaining best practices for scalability, reliability, security, and operational excellence.
• Implement and maintain model registries, experiment tracking, versioning, and governance practices to support consistent model lifecycle management.
• Build and support containerized ML workloads and deployment workflows using technologies such as Docker and Kubernetes.
• Develop monitoring, observability, and alerting capabilities for machine learning systems, including model performance tracking, drift detection, and data quality monitoring.
• Collaborate with Machine Learning Engineers, Data Scientists, Software Engineers, and Infrastructure teams to operationalize ML solutions and improve deployment efficiency.
• Implement and maintain IaC patterns using Terraform.
• Troubleshoot and resolve complex technical challenges related to model deployment, ML infrastructure, and production operations.
• Provide guidance and mentorship to other engineers.

What You Need to Succeed:

• Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence or related field or equivalent experience.
• 4+ years of professional experience in software engineering, machine learning engineering, MLOps, platform engineering, DevOps, or a related technical discipline.
• Strong understanding of the machine learning lifecycle, including model training, validation, deployment, monitoring, and retraining.
• Experience building and maintaining automated machine learning pipelines and CI/CD workflows.
• Experience with MLOps platforms and tools such as MLflow, Kubeflow, Azure Machine Learning, Databricks, or similar technologies.
• Experience in Python programming, ML Framework and Agentic AI. Implemented model monitoring, experiment tracking, model versioning, and governance practices.
• Experience working with cloud-based machine learning solutions, preferably within Azure.
• Ability to independently solve complex technical challenges, make sound decisions with minimal guidance, and drive work to completion.

Ready to Join? Apply now at myparadigm.com/careers/