Anduril
Senior Machine Learning Engineer (Applied Intelligence)
$220K–$292K
Santa Ana, California, United States · Senior · Full-time · Posted Oct 15, 2026
- Experience
- 6+ years in software engineering or ML engineering roles building production systems.
- Education
- Degree in Computer Science, Engineering, or related technical field, or equivalent practical experience.
About the job
Owns the infrastructure and production operations that take machine-learning prototypes into reliable systems serving manufacturing teams across cloud and factory-floor environments.
What you'll do
- Build, deploy, monitor, and maintain ML systems across cloud and on-premises factory environments, including on-call incident response.
- Develop the ML platform and lifecycle infrastructure for data pipelines, datasets, training, model serving, governance, and observability.
- Translate requirements across ML, data engineering, enterprise, and manufacturing teams into production infrastructure and operational practices.
What they ask for
- Strong production MLOps experience and a track record of taking ML models from prototype to production and maintaining them.
- Experience with on-call rotations and production incident management for data or ML systems.
- Proficiency in Python; experience with PyTorch or TensorFlow, Docker, and Kubernetes.
- U.S. Person status required to access export-controlled data.
Nice to have
- Experience in manufacturing, industrial, or OT-adjacent domains; or deploying ML to edge/on-premises hardware.
- Experience with workflow/orchestration tools such as Flyte, Airflow, Kubeflow, or Temporal.
Pay
$220,000 — $292,000 USD (base salary)
Tools
Python, PyTorch, TensorFlow, Docker, Kubernetes, Flyte, Airflow, Kubeflow
AI focus
Productionize and operate ML systems for manufacturing, including model inference, monitoring, drift detection, and lifecycle governance.
Model-written summary · the original posting is authoritative