ML Infrastructure Engineer

Mach9 builds production AI systems for civil engineering and surveying, using large-scale survey data, image segmentation, and 3D prediction models. The ML Infrastructure Engineer will build and maintain training pipelines, data and model versioning systems, CI/CD workflows, and scalable inference infrastructure for offline and real-time applications.

Responsibilities:

• Design and build a centralized system for versioning training data, generated datasets, and model artifacts, with full lineage tracking from raw source data through to trained model outputs
• Develop and maintain reliable, reproducible ML training and data generation pipelines
• Refactor and harden existing training and data generation scripts into composable, testable, and maintainable components
• Create CI/CD workflows for validating data pipelines and model training runs, including automated correctness checks and regression detection
• Build tooling that enables ML engineers to launch, monitor, and debug training jobs with minimal friction
• Optimize and scale real-time model inference services to meet latency and throughput requirements in production, including profiling, batching strategies, and resource-efficient serving
• Own the deployment path from trained model artifact to production endpoint, ensuring reliable rollouts, rollback, and monitoring