ML Infrastructure Engineer
Hybrid (San Francisco)$160k - $250kFull-timePosted 2w ago
About the role
ML infrastructure engineer role at Mach9 building and maintaining the systems powering production AI models for civil engineering and surveying, spanning training pipelines, data/versioning, and real-time inference integrated with CAD software.
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 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.
Qualifications
- 3+ years of work experience in relevant fields.
- Bachelor's or Master's degree in Computer Science, Engineering, or equivalent experience.
- Strong communication skills and ability to work closely with ML researchers and engineers to translate workflows into robust systems.
- Experience designing and building data versioning, artifact management, or dataset lineage systems (e.g., DVC, LakeFS, Weights & Biases, or custom solutions).
- Hands-on experience with ML pipeline orchestration tools (e.g., Airflow, Prefect, Metaflow, or similar).
- Experience with model serving and inference optimization — profiling latency, reducing memory footprint, or scaling serving infrastructure to meet real-time constraints.
- Ability to read and refactor ML training code to understand training pipelines and improve reliability.
- Proficient with Python, PyTorch.
Skills
Required:PythonPyTorch
Benefits
- N/A
Last updated Oct 21, 2026. Interested? Apply on the company site.
About Mach9
The Fastest Tool for Automating Geospatial Production
Mach9 is at the forefront of leveraging advanced machine learning and computer vision techniques to transform geospatial data into actionable insights for urban development and infrastructure management. Our cutting-edge technology automates the detection and analysis of key urban features, aiding in the planning and maintenance of transportation networks.
machine-learningcomputer-visioninfrastructureai
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