Senior Machine Learning Engineer, Applied Intelligence
Anduril Industries · Santa Ana, California, United States
About this role
**Senior Machine Learning Engineer, Applied Intelligence** **About Anduril** Anduril Industries is a defense technology company transforming U.S. and allied military capabilities with advanced technology. Lattice OS, an AI-powered operating system, powers Anduril's family of systems, turning thousands of data streams into realtime 3D command and control. **About the Team** Maritime Digital Production (MDP) builds the full technology stack powering Anduril's shipbuilding factories—from data infrastructure and manufacturing execution systems to scheduling engines and AI systems. Operating at the boundary between Operational Technology and Information Technology, MDP is scaling from a founding team to 70+ engineers across multiple U.S. sites. **The Role** Architect and operate the AI/ML platform stack powering ML pipelines for factory sensing, document processing, and intelligent automation. Build infrastructure that operationalizes computer vision, NLP, and RAG-enabled tools with production-grade workflows and human-in-the-loop controls. **Key Responsibilities** • Architect end-to-end AI/ML platform stack (data ingestion, labeling, feature engineering, model training, deployment, monitoring) • Select and standardize industrial AI components (feature stores, vector databases, OCR/IDP, computer vision serving, orchestration) • Build model-serving frameworks optimized for production across cloud, edge, and shop-floor systems • Partner with manufacturing engineers to translate production workflows into MLOps requirements • Implement event-driven data pipelines and telemetry systems • Deploy and operate systems in factory environments including edge compute and OT networks • Define model governance processes for validation, safety reviews, and traceability • Lead reliability engineering for deployed models (drift detection, retraining, alerting) • Mentor junior engineers and establish MLOps best practices **Required Qualifications** • 8+ years software engineering experience building production systems • Deep MLOps expertise with end-to-end production AI/ML delivery • Strong Python proficiency and deep learning frameworks (PyTorch, TensorFlow) • Docker and Kubernetes containerization experience • Data engineering, time-series modeling, and semantic data systems expertise • Model observability, inference accuracy, and data drift implementation • Event-driven architectures and real-time systems integration experience • Strong stakeholder management and cross-team collaboration skills • CS/Engineering degree or equivalent practical experience • U.S. Person status required (export controlled data access) **Preferred Qualifications** • Manufacturing, industrial, or OT domain experience (MES, SCADA, PLC, factory automation) • AI/ML application in manufacturing, logistics, or production environments • Digital twins, predictive maintenance, OCR/IDP, or computer vision experience • Workflow orchestration tools (Flyte, Airflow, Kubeflow, Temporal) • GPU acceleration (CUDA) and inference optimization (TensorRT, Triton) • RAG systems and vector database experience • Hyper-growth startup environment experience • Enterprise systems familiarity (ERP, MES, WMS, PLM) • Regulated environment experience (NNPI/ITAR) • Secret clearance eligibility **Compensation** 💰 $220,000 – $292,000 USD + competitive equity + top-tier benefits
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