Senior Machine Learning Engineer (Applied Intelligence)
Senior ML Engineer on Anduril's Maritime Digital Production team, owning the MLOps infrastructure that turns factory-floor ML prototypes into reliable 24/7 production systems across cloud and on-prem OT environments. Core stack: Python, PyTorch/TensorFlow, Docker/Kubernetes, data pipelines, monitoring and drift detection.
- Compensation
- $220K–$292K / yr
- Location
- Santa Ana, California, United States
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Full time
- Experience
- 6+ years
- Category
- Ml / AI
- Posted
Skills
Must have
- 6+ years in software or ML engineering building production systems
- Strong production MLOps experience: data pipeline management, model versioning, deployment automation, production monitoring
- Track record taking ML models from prototype to production and maintaining long-term
- Experience with on-call rotations and production incident management for data/ML systems
- Proficiency in Python and deep learning frameworks (PyTorch, TensorFlow)
- Building and deploying containerized ML services with Docker and Kubernetes
- Data engineering skills: pipeline orchestration, data quality, time-series or event-driven data
- Observability for model performance, inference accuracy, and data drift
- Strong technical communication across ML research, data engineering, and operations
- Experience building systems reliable under real-world operational constraints (high availability, low latency)
- Proven ability to coordinate across teams and translate requirements into technical solutions
- Degree in Computer Science, Engineering, or related field, or equivalent experience
- U.S. Person status required for access to export controlled data
Nice to have
- Experience in manufacturing, industrial, or OT-adjacent domains (MES, SCADA, factory automation, IoT)
- Deploying ML models to edge devices or on-premises hardware in production
- Workflow/orchestration tools such as Flyte, Airflow, Kubeflow, or Temporal
- GPU infrastructure management and inference optimization (TensorRT, Triton Inference Server)
- MLOps tools: experiment tracking (MLflow, Weights & Biases), feature stores (Feast, Tecton), model registries
- Building RAG systems, vector databases (Pinecone, Weaviate, Milvus), or LLM deployment pipelines
- Computer vision deployment, OCR/IDP systems, or document processing pipelines
- Coordinating with platform/infrastructure teams at larger organizations
- Event-driven architectures, IoT/UNS patterns, real-time systems integration
- Edge ML deployment, model optimization (quantization, pruning), resource-constrained devices
- Experience in regulated environments (NNPI/ITAR) and secure model/data governance
- Experience in hyper-growth startup environments
- Familiarity with enterprise systems such as ERP, MES, WMS, or PLM
- Eligible to obtain and maintain a U.S. Secret security clearance
Full description
Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.
ABOUT THE TEAM
Maritime Digital Production (MDP) is the software and digital systems function within Anduril's Heavy Metal division. We build and deploy the full technology stack that powers Anduril's shipbuilding factories: the data infrastructure that makes every machine and sensor visible in real time, the manufacturing execution system (ArsenalOS) that workers and planners use every shift, the scheduling engine that replans production in minutes instead of days, and the AI systems that eliminate manual toil from both the shop floor and business operations.
MDP operates at the boundary between Operational Technology and Information Technology. Our systems live where factory-floor machines, edge compute, and OT networks meet enterprise platforms and cloud infrastructure. We incubate solutions close to the production line, validate them with real operators building real hardware, harden them for reliability and security, and then scale them across multiple sites. The environment is fast, physical, and consequential. When our systems go down, production stops. The output of our work is not a dashboard: it is a ship.
This is not a support function. It is a strategic investment by Anduril in the premise that digitizing the manufacturing lifecycle end-to-end, from engineering definition through scheduling through execution through field feedback, is how Heavy Metal will out-build, out-adapt, and out-scale the traditional defense industrial base. MDP is scaling from a founding team to 70+ engineers across multiple U.S. sites. You will be joining early, working on hard problems with real operational stakes, and shaping how manufacturing software is built at Anduril from the ground up.
ABOUT THE JOB
As a Machine Learning Engineer on the Applied Intelligence initiative, you will be the critical bridge between ML research and production operations. You will own the infrastructure that brings ML prototypes from concept to reliable, production-grade systems running on factory floors and serving manufacturing teams. Working at the intersection of data engineering, MLOps, and production operations, you'll execute the vision of ML engineers by building robust datasets, training infrastructure, and inference systems that operate reliably in both cloud and on-premises OT environments.