Production ML Engineer — Edge & OT Platform Lead

Anduril-1; Santa Ana (CA); On-site; USD 220,000 - 292,000; Full time

Benefits offered by this job

Equity grants

Competitive benefits

Job summary

Anduril Industries is seeking a Machine Learning Engineer to bridge ML research and production, owning infrastructure that brings prototypes to reliable systems on factory floors. You will translate ML requirements into scalable infrastructure, coordinate with data engineering, manufacturing operations, and enterprise teams, and ensure 24/7 reliability in real environments.

You will lead the end-to-end ML platform development, including data pipelines, training orchestration, and model serving

Qualifications

• 6+ years of software/ML engineering experience
• Strong production MLOps experience: pipelines, versioning, deployment, monitoring
• Proven ability to take ML models from prototype to production
• Experience with on-call rotations and production incident management
• Proficiency in Python; experience with PyTorch/TF
• Experience building containerized ML services (Docker, Kubernetes)
• Solid data engineering and time-series/event-driven data handling
• Experience with observability for model performance and data drift
• Excellent cross-team technical communication
• Ability to operate in high-availability, low-latency environments
• Coordinate across multiple teams to translate requirements into solutions
• Degree in CS/Engineering or equivalent
• U.S. Person status required

Responsibilities

• Own production hardening and deployment of ML apps
• Participate in on-call rotations for deployed ML products
• Build and maintain inference infrastructure across cloud and on-premise OT
• Deploy and operate ML systems in factory environments including edge clusters
• Implement monitoring, alerting, and drift detection for production ML
• Define rollback procedures and safety reviews for AI systems
• Interface with data engineering to define ML 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 based on needs
• Architect end-to-end ML platform from data ingestion to model lifecycle
• Support real-time and batch model serving across environments
• Design training infrastructure enabling reproducibility and governance
• Own dataset creation, curation, and versioning
• Implement model governance, retraining triggers, and artifact management
• Write production-quality code with tests, participate in reviews
• Mentor junior engineers and data scientists

Skills

Python

Deep learning (PyTorch/TF)

MLOps

Docker & Kubernetes

On-call incident management

Data engineering

Model governance

Technical communication

Education

BS in Computer Science / Engineering

Tools

Docker

Kubernetes

Flyte/Airflow/Kubeflow

Job description

Anduril Industries is seeking a Machine Learning Engineer to bridge ML research and production, owning infrastructure that brings prototypes to reliable systems on factory floors. You will translate ML requirements into scalable infrastructure, coordinate with data engineering, manufacturing operations, and enterprise teams, and ensure 24/7 reliability in real environments.

You will lead the end-to-end ML platform development, including data pipelines, training orchestration, and model serving