Senior ML Engineer — Production & Edge AI (Onsite)

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

Job summary

Anduril Industries in Santa Ana, CA, seeks an experienced ML/Software engineer to own the production hardening and deployment of ML prototype applications for manufacturing operations. You will bridge ML research with production-grade systems across cloud and on-prem OT environments, and serve as the on-call owner for deployed ML systems.

You will build end-to-end ML platform capabilities and collaborate with data engineers, manufacturing engineers, and enterprise teams to ensure reliable,

Qualifications

• 6+ years of experience building production ML/AI systems in fast-paced environments.
• Strong production MLOps experience including data pipelines, model versioning, deployment automation, and monitoring.
• Experience taking ML models from prototype to production and maintaining them long-term.

Responsibilities

• Own production hardening and deployment of ML prototype applications for manufacturing operations.
• Serve as on-call owner for deployed ML systems and build end-to-end ML platform capabilities across cloud and OT environments.
• Interface with data engineering to define and deliver ML-specific data infrastructure needs for Applied Intelligence.
• Coordinate with enterprise teams to secure compute resources, labeling infrastructure, data access, and modeling capabilities.
• Design training infrastructure that supports fast iteration while ensuring reproducibility and governance.

Skills

Python

PyTorch

TensorFlow

Docker

Kubernetes

MLOps

On-call rotations

Education

Bachelor's degree in Computer Science or related field

Tools

Flyte

Airflow

Kubeflow

Temporal

MLflow

Job description

Anduril Industries in Santa Ana, CA, seeks an experienced ML/Software engineer to own the production hardening and deployment of ML prototype applications for manufacturing operations. You will bridge ML research with production-grade systems across cloud and on-prem OT environments, and serve as the on-call owner for deployed ML systems.

You will build end-to-end ML platform capabilities and collaborate with data engineers, manufacturing engineers, and enterprise teams to ensure reliable,