Senior ML Ops Engineer (Machine Learning Infrastructure)

Parallel Systems is seeking a Senior MLOps Engineer to lead the design and development of scalable ML infrastructure for autonomous battery-electric rail vehicles. The role involves building robust MLOps pipelines, managing distributed training and inference, and collaborating with ML and robotics teams. This is a hybrid position with at least one week per month onsite in Los Angeles.

• Design and implement robust MLOps solutions, including automated pipelines for data management, model training, deployment and monitoring.
• Architect, deploy, and manage scalable ML infrastructure for distributed training and inference.
• Collaborate with ML engineers to gather requirements and develop strategies for data management, model development and deployment.
• Build and operate cloud-based systems (e.g., AWS, GCP) optimized for ML workloads in R&D and production environments.
• Build scalable ML infrastructure to support continuous integration/deployment, experiment management, and governance of models and datasets.
• Support the automation of model evaluation, selection, and deployment workflows.

• Bachelor’s or higher degree in Computer Science, Machine Learning, or a relevant engineering discipline.
• 5+ years of experience building large-scale, reliable systems; 2+ years focused on ML infrastructure or MLOps.