Senior Mlops Engineer

FreightVerify is a leading Software-as-a-Service (SaaS) company that is transforming the supply chain and distribution industries with data-driven insights. By leveraging network visibility, we empower businesses with optimizations and recommendations that enhance efficiency and performance. We are seeking an experienced Senior MLOps Engineer to enhance our ML/AI infrastructure and work with our cross-functional teams to deliver scalable, reliable, and efficient machine learning systems.

Job Summary

As a Senior MLOps Engineer, you will be responsible for the end-to-end deployment, scaling, and maintenance of machine learning models, as well as the data pipelines that support them. This hands-on role requires strong expertise in cloud-native MLOps and data engineering, with a focus on automation, observability, and cross-functional collaboration. Your work will help operationalize machine learning at scale, ensuring high reliability and seamless integration within our multi-cloud environment.

Note: This position is located in Ann Arbor, MI and requires onsite work. 

Primary Responsibilities:

• Design, deploy, and manage scalable data pipelines for AI/Machine Learning, integrating with tools like Kubernetes, EMR, Databricks, and Luigi.

• Collaborate with data engineering, business analysts, product owners, and other engineering teams to align on requirements and deliver robust ML solutions.

• Build and maintain automated CI/CD pipelines for model deployment, versioning, and monitoring.

• Ensure cross-cloud compatibility and optimize multi-cloud architectures (AWS, Azure).

• Use and manage tools such as Kubeflow, Airflow, and MLflow for pipeline orchestration, experiment tracking, and deployment.

• Implement monitoring and observability tools for model performance, data drift, and reliability using Prometheus, Grafana, and Evidently AI.

• Leverage Kafka for efficient data streaming and real-time processing capabilities within AI/Machine Learning pipelines.

• Conduct regular code and infrastructure reviews, prioritizing maintainability and scalability.

• Stay hands-on with programming, mostly using Python, where appropriate to support Spark-based workflows.

Qualifications

• 5-10 years of experience in MLOps, with a strong background in cloud-native machine learning, data engineering, and automation.
• Proficiency in Python.
• Experience with best-in-class tools for MLOps and data engineering, such as EMR, Databricks, Luigi, Kafka, MLflow, and Airflow.
• Proven experience with CI/CD pipelines and testing frameworks for model and pipeline deployment.
• Hands-on experience with multi-cloud environments, especially AWS and Azure.
• Strong understanding of observability, monitoring, and model drift detection.
• Solid grasp of DevOps principles, with practical experience in production-level model and data pipeline support.
• Excellent problem-solving skills and ability to work effectively in a collaborative environment.

Why Join Us?

• Be part of an innovative team that’s making a real impact on supply chain and logistics optimization.
• Work with cutting-edge MLOps tools and multi-cloud architectures.
• Enjoy growth opportunities within a company that values technical leadership and creative problem-solving.