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Anduril Industries is a defense technology company transforming military capabilities through advanced autonomy, AI, and sensor fusion. The Maritime Digital Production (MDP) team builds the full technology stack powering Anduril's shipbuilding factories, operating at the intersection of operational technology and IT.
As a Senior IoT Engineer on the Applied Intelligence initiative, you will design, build, and deploy connected sensor infrastructure and edge intelligence systems that power ML pipelines for factory sensing, document processing, and drawing conversion. You'll develop IoT-enabled data collection systems feeding computer vision, NLP, and RAG-enabled AI workflows, creating intelligent sensing capabilities across the manufacturing environment.
Key responsibilities include:
- Design and deploy IoT sensor networks and edge devices capturing real-time factory data for ML pipelines, including computer vision systems, document processing, and production monitoring
- Develop edge intelligence systems running ML inference locally on IoT devices for real-time factory sensing, quality inspection, and anomaly detection
- Partner with manufacturing engineers and factory operators to translate production workflows into IoT sensing and data collection requirements
- Write production-quality code with comprehensive tests, participating in code review and architectural discussions
- Implement secure, scalable IoT communication architectures using industrial protocols (MQTT, AMQP, OPC-UA, Sparkplug B)
- Build data ingestion pipelines connecting IoT sensors, cameras, and edge devices to ML model serving infrastructure
- Design edge compute architectures supporting on-device ML inference, local data processing, and intermittent connectivity in factory environments
- Deploy and operate systems in factory environments, including edge compute clusters and OT networks
- Develop firmware and embedded software for microcontrollers, single-board computers (Raspberry Pi, NVIDIA Jetson), and industrial IoT gateways
- Implement cybersecurity best practices including device authentication, encryption, secure boot, and PKI
- Leverage AI tooling in development workflow and contribute to team engineering practices
- Join on-call rotation supporting production factory systems
Required: 5+ years building production systems in fast-paced environments, deep IoT systems engineering expertise (embedded development, edge computing, IoT cloud architectures), strong software architecture fluency (APIs, distributed systems, CI/CD, cloud/edge infrastructure), proficiency in C, C++, Python, or JavaScript/Node.js, hands-on microcontroller and single-board computer experience, and deep understanding of IoT communication protocols.
