Senior Machine Learning Engineer, Applied IntelligenceActive$292K

Anduril Industries
Apply now

The opportunity

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…

What you'll do

  • Architect and own the AI/ML platform stack—from data ingestion, labeling, and: feature engineering to model training, deployment, monitoring, and lifecycle management for factory sensing and intelligent automation applications.

  • Select, prioritize, and standardize industrial AI components including: feature stores, vector databases for RAG pipelines, OCR/IDP and computer vision model serving, orchestration layers, and observability systems.

  • Build model-serving and inference frameworks optimized for production: environments, supporting real-time and batch execution across cloud, edge, and shop-floor systems.

  • Partner with manufacturing engineers and factory operators to understand: production workflows and translate them into MLOps requirements.

  • Write production-quality code with comprehensive tests, participating in code: review and architectural discussions.

  • Translate factory scenarios (quality inspection, receiving, root-cause: analysis, document processing) into applied AI workflows with defined human-in-the-loop gates, audit trails, and integration contracts with PLM, MES, ERP, and the unified data plane.

What they're looking for

  • Experience in manufacturing, industrial, or OT-adjacent domains (MES, SCADA,: PLC integration, factory automation, IoT).
  • Experience applying AI/ML within manufacturing, logistics, industrial control, or production environments.
  • Background with digital twins, predictive maintenance, OCR/IDP, computer: vision, or speech-to-text model integrations.
  • Experience with workflow/orchestration tools such as Flyte, Airflow, Kubeflow, or Temporal.
  • Familiarity with GPU acceleration (CUDA) and inference optimization (TensorRT, Triton Inference Server).
  • Experience building RAG (Retrieval-Augmented Generation) systems, vector: databases (Pinecone, Weaviate, Milvus), and LLM deployment pipelines.
  • Familiarity with frontier AI tooling, AI coding assistants, and AI-enabled software development workflows.
  • Experience in hyper-growth startup-like environments, with demonstrated: success balancing speed, ambiguity, and long-term system health.