Production ML Engineer: Edge, OT & On-Call

Anduril Industries, Inc.; Santa Ana (CA); On-site; USD 220,000 - 292,000; Full time

Job summary

Anduril Industries, Inc. is seeking a Machine Learning Engineer for the Applied Intelligence initiative to bridge ML research and production on the factory floor.

You will own infrastructure turning prototypes into reliable, scalable systems across cloud and on-prem OT environments, partnering with data engineering, manufacturing ops, and enterprise teams. You’ll ensure 24/7 reliability with strong governance.

Qualifications

• 6+ years of experience in software or ML engineering roles building production systems
• Strong production MLOps experience: data pipeline management, model versioning, deployment automation, and production monitoring
• Proven track record of taking ML models from prototype to production and maintaining them long-term
• Experience with on-call rotations and production incident management for data or ML systems
• Strong proficiency in Python and experience with deep learning frameworks (PyTorch, TensorFlow)
• Experience building and deploying containerized ML services using Docker and Kubernetes
• Solid data engineering skills including pipeline orchestration and data quality management
• Experience implementing observability for model performance, inference accuracy, and data drift
• Strong technical communication skills across ML research, data engineering, and operations teams
• Experience operating in high-availability, low-latency production environments
• Degree in CS/Engineering or related field, or equivalent practical experience
• U.S. Person status is required for export controlled data access

Responsibilities

• Own production hardening and deployment of ML prototype applications to reliable production systems
• Participate in on-call rotations for deployed ML products on factory floors with high availability
• Build and maintain inference infrastructure across cloud and on-prem OT hardware
• Deploy ML systems in factory environments with edge compute and OT networks
• Implement monitoring, alerting, and drift detection to maintain production SLOs
• Define rollback procedures and safety reviews for AI systems in production
• Interface with data engineering to deliver ML-specific data infrastructure
• Coordinate with enterprise teams to secure compute resources and labeling infrastructure
• Translate ML requirements into infrastructure for datasets, training and inference
• Collaborate with manufacturing engineers to align ML with production workflows
• Drive make/buy decisions against Applied Intelligence needs
• Architect end-to-end ML platform from data ingestion to model lifecycle management
• Build model-serving frameworks for real-time and batch execution
• Implement event-driven data pipelines feeding real-time signals from sensors
• Standardize MLOps components including feature stores and model registries
• Design training infrastructure enabling fast iterations with reproducibility
• Own dataset creation, curation, versioning and governance
• Establish data labeling workflows and continuous data monitoring
• Manage model versioning and artifact management across environments
• Write production-quality code with tests and code reviews
• Promote best practices for MLOps, observability and secure data handling
• Mentor junior engineers and data scientists on production ML practices

Skills

Python

ML engineering

On-call rotations

Production systems

Technical communication

Education

Bachelor's degree in CS/Engineering or related field

Tools

Docker

Kubernetes

Flyte

Airflow

Kubeflow

Temporal

Job description

Anduril Industries, Inc. is seeking a Machine Learning Engineer for the Applied Intelligence initiative to bridge ML research and production on the factory floor.

You will own infrastructure turning prototypes into reliable, scalable systems across cloud and on-prem OT environments, partnering with data engineering, manufacturing ops, and enterprise teams. You’ll ensure 24/7 reliability with strong governance.