Senior Machine Learning Engineer, Applied Intelligence

Maritime Digital Production (MDP) is the software and digital systems function within Andurils Heavy Metal division. We build and deploy the full technology stack that powers Andurils 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.

As a Senior ML Engineer on the Applied Intelligence initiative you will help architect and operate the AI/ML platform stack that powers ML pipelines for factory sensing document processing and intelligent automation. You will help build the infrastructure that operationalizes computer vision NLP and RAG-enabled tools translating factory scenarios into production-grade AI workflows with clear human-in-the-loop controls and enterprise system integrations.

• Architect and own the AI/ML platform stackfrom 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.
• Implement event-driven data pipelines and telemetry systems that feed models with contextualized real-time signals from factory sensors production systems and logistics operations.
• Deploy and operate your systems in factory environments including edge compute clusters and OT networks.
• Drive make/buy strategy by researching internal and vendor AI capabilities and recommending investments aligned to enterprise roadmaps Anduril IP principles and production constraints.
• Define and maintain model governance processes for validation safety reviews traceability and rollback procedures for AI systems in production.
• Lead reliability engineering for deployed modelsmanaging drift detection retraining triggers alerting and operational SLOs for factory sensing and document processing applications.
• Leverage AI tooling (coding assistants automation) in your development workflow and contribute to team engineering practices.
• Join an on-call rotation supporting production factory systems.
• Mentor junior engineers and data scientists; establish best practices for MLOps observability data management and secure handling of sensitive production data.

• 8 years of experience in a software engineering role building production systems ideally in a fast-paced environment.
• Deep expertise in MLOps with end-to-end experience delivering production-grade AI/ML systems.
• Strong technical fluency in modern software architectures APIs distributed systems CI/CD and cloud or edge infrastructure.
• Deep experience with MLOps: data acquisition labeling curation pipeline management model versioning continuous integration and model monitoring.
• Strong proficiency in Python and experience with deep learning frameworks (PyTorch TensorFlow).
• Experience building and deploying containerized ML services using Docker and Kubernetes.
• Proficiency in data engineering time-series data modeling and working with semantic/ontology-driven data systems.
• Experience implementing observability for model performance inference accuracy and data drift.
• Familiarity with event-driven architectures IoT/UNS patterns and real-time systems integration.
• Experience building systems that must operate reliably under real-world operational constraints (high availability low latency or constrained environments).
• Strong stakeholder management skills with proven experience aligning engineering data and manufacturing teams.
• Excellent written and verbal communication skills; able to bridge research platform and production domains and collaborate across engineering manufacturing and operations teams.
• Degree in Computer Science Information Systems Engineering or related technical field or equivalent practical experience.
• U.S. Person status is required as this position needs to access export controlled data.

• 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.
• Familiarity with enterprise systems such as ERP MES WMS PLM or manufacturing planning systems.
• Experience in regulated environments (NNPI/ITAR) and secure model/data governance.
• Demonstrated ability to mentor engineers and set technical direction for AI/ML infrastructure at scale.
• Experience with MLOps tools including experiment tracking (MLflow Weights & Biases) feature stores (Feast Tecton) and model registries.
• Experience in manufacturing industries with hands-on exposure to assembly lines or production environments.
• Knowledge of edge ML deployment model optimization (quantization pruning) or deploying models on resource-constrained devices.
• Eligible to obtain and maintain a U.S. Secret security clearance.

The salary range for this role is an estimate based on a wide range of compensation factors inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience education and/or training critical skills and/or business considerations. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Andurils total compensation package. Additionally Anduril offers top-tier benefits for full-time employees including:

At Anduril we invest in our people. Our comprehensive competitive benefits package (available at little to no cost to employees) ensures youre supported in health recovery and whatever comes next.For more information Explore Our Benefits.

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