Anduril Industries
Software Engineer - ML Infrastructure
About this role
Anduril Industries seeks a Software Engineer for ML Infrastructure to develop core systems powering perception and autonomy across their AI-driven defense platform. You'll build data management, model training orchestration, and dataset curation infrastructure while partnering with perception engineers to operationalize frontier models at scale.
What you'll do
- Own and operate core model training and dataset management infrastructure for perception systems
- Develop perception engineer-facing SDKs and tooling to improve model training and evaluation workflows
- Integrate frontier models into data augmentation, curation, and synthetic data generation pipelines
- Build observability systems for ML lifecycle monitoring, evaluation reporting, and model registry
- Design systems for semantic search and querying across multi-modal sensor datasets
- Collaborate with business line teams to understand data requirements and deliver solutions
What they're looking for
- Python (strong proficiency)
- Rust and Python interoperability (PyO3, Maturin)
- Deep learning frameworks (TensorFlow, PyTorch)
- Distributed training and MLOps orchestration (Modal, Flyte, Airflow, Dagster)
- ML observability platforms (Weights & Biases, MLFlow)
- Kubernetes and backend service deployment
- Data management and indexing systems
- Edge deployment and model optimization
Benefits
- Competitive equity grants
- Top-tier benefits for full-time employees
- Access to cutting-edge AI and autonomy technology
- Opportunity to impact military capabilities
- Collaborative environment with perception engineers
- Work with frontier models and advanced sensor fusion
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Anduril Industries
Anduril Industries builds autonomous defense systems including underwater vehicles, unmanned aircraft, and electronic warfare platforms for the Department of Defense. The company is hiring across mechanical engineering, mission operations, software development, technical leadership, and advanced manufacturing roles to support the design, deployment, and production of these mission-critical systems.
- Website
- anduril.com
Likely interview questions
- Can you describe your experience building or operating ML training infrastructure at scale, and how you've addressed reliability and performance challenges?
- Tell us about a time you developed SDKs or tooling for internal engineers—how did you gather requirements and iterate on the design?