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Staff AI Infrastructure Engineer

Anduril· Air Dominance & Strike : Mission Autonomy Engineering : Mission Software Engineering
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Hybrid (Costa Mesa, CA), Hybrid (Seattle, WA), Hybrid (Washington, DC)$220k - $292kfull-timePosted 2mo ago

About the role

Founding Staff AI Infrastructure Engineer to architect, build, and scale the end-to-end machine learning platform powering Anduril’s autonomous systems, enabling training, evaluation, hosting, and serving of complex AI models in cloud and air-gapped edge environments.

Responsibilities

  • Design, build, and maintain our foundational training, orchestration, and experimentation infrastructure to support state-of-the-art model development.
  • Actively identify, measure, and eliminate bottlenecks in the ML research lifecycle. Build highly automated tools for hyperparameter tuning, model profiling, and experimentation tracking.
  • Design and scale robust, high-performance ETL pipelines capable of processing terabytes of multi-modal data (video, camera feeds, radar, flight telemetry, and simulation logs) captured from physical assets and test sites.
  • Architect high-throughput, low-latency model serving frameworks optimized for both scalable cloud environments and air-gapped, resource-constrained tactical edge environments. Build CI/CD pipelines for ML models with automated validation, canary deployments, and rollback capabilities.
  • Build robust, automated pipelines for continuous evaluation, model validation, and reinforcement learning alignment loops (RLHF/DPO) to guarantee model safety and predictability in high-stakes environments.
  • Work closely with AI Researchers, Computer Vision teams, and platform engineers to design unified infrastructure standards across the company's autonomous systems programs.

Qualifications

  • 7+ years of software engineering experience with a proven track record of designing, building, and operating production-scale machine learning systems and platforms (MLOps).
  • Proficient in Python, Go, C++, or similar backend languages. Deep understanding of ML systems design, memory management, and distributed computing.
  • Deep experience with containerized deployments (Docker, Kubernetes), GPU scheduling/orchestration, and distributed training frameworks (e.g., PyTorch Distributed, Ray, Slurm, or Megatron-LM).
  • Hands-on experience building distributed data pipelines (ETL) and managing massive datasets (terabytes of unstructured/multi-modal sensor data).
  • Experience setting technical direction, leading complex system migrations, and mentoring senior engineers.
  • Eligible to obtain and maintain an active U.S. Top Secret security clearance.

Skills

Required:ML platform design and developmentPythonGo/C++Containerization and orchestrationDistributed training frameworksETL pipelinesModel serving & CI/CD for MLSecurity clearance

Benefits

  • Benefits information described in the job post: comprehensive, competitive benefits package available at little to no cost to employees.
Last updated Aug 26, 2026. Interested? Apply on the company site.

About Anduril

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