Senior ML Engineer — Production ML & Edge AI

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

Job summary

Anduril Industries seeks a Machine Learning Engineer for the Applied Intelligence initiative. You will bridge ML research and production, owning infrastructure that brings ML prototypes to reliable production-grade systems on factory floors and OT environments.

You will work across data engineering, MLOps, and manufacturing operations to build robust datasets, training infra, and inference pipelines that run in cloud and on-premises settings.

Qualifications

• 6+ years of experience in software or ML engineering building production systems.
• Strong production MLOps: data pipelines, model versioning, deployment automation, monitoring.
• Proven track record of taking ML models from prototype to production and maintaining them.
• Experience with on-call rotations and production incident management for data/ML systems.
• Proficiency in Python and deep learning frameworks (PyTorch, TensorFlow).
• Experience deploying containerized ML services with Docker and Kubernetes.

Responsibilities

• Own production hardening and deployment of ML prototype applications.
• Part of on-call rotations for deployed ML products on factory floors; ensure high availability.
• Build and maintain inference infrastructure across cloud and on-premises OT hardware.
• Deploy and operate ML systems in factory environments with edge compute clusters.
• Implement monitoring, alerts, and drift detection to maintain SLOs for production ML apps.
• Define rollback procedures, validation gates, and safety reviews for AI systems in production.
• Interface with data engineering to deliver ML-specific data infrastructure needs.
• Coordinate with enterprise teams to secure compute resources and data access.
• Translate ML requirements into infrastructure for datasets, training pipelines, and inference systems.
• Drive make/buy decisions for Applied Intelligence needs.
• Architect end-to-end ML platform stack (data ingestion to model serving and lifecycle).
• Build model-serving/inference frameworks for real-time and batch execution across cloud/edge/shop-floor.
• Design data pipelines and telemetry systems feeding models with real-time signals.
• Standardize MLOps components (feature stores, vector databases, registries, orchestration, observability).
• Develop training infrastructure enabling rapid iteration with reproducibility.

Skills

Python

ML engineering

Production ML

Docker

Kubernetes

PyTorch

TensorFlow

Data pipelines

Time-series data

On-call incident management

Education

BS in CS/Engineering

Tools

Flyte

Airflow

Kubeflow

Temporal

MLflow

Weights & Biases

Job description

Anduril Industries seeks a Machine Learning Engineer for the Applied Intelligence initiative. You will bridge ML research and production, owning infrastructure that brings ML prototypes to reliable production-grade systems on factory floors and OT environments.

You will work across data engineering, MLOps, and manufacturing operations to build robust datasets, training infra, and inference pipelines that run in cloud and on-premises settings.