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Anduril Industries

Staff AI Infrastructure Engineer

Anduril Industries · Costa Mesa, California, United States; Seattle, Washington, United States; Washington, District of Columbia, United States

Posted 28 days ago

or apply directly on Anduril Industries's site. We never take the application ourselves.

Is this posting real?

This role has been open
28 days
Anduril Industries's roles stay open a median of 45 days
Reposted
No
Salary listed
No
1% of Anduril Industries's roles list one
Ghost-job risk at Anduril Industries
high
1390 stale, 67 reposted of 2,263 open
Hiring momentum
3233 roles opened in the last 90 days
↑ up vs. the prior 90 days
Last confirmed on the employer's board
2026-09-17

Measured from postings appearing on and disappearing from Anduril Industries's own greenhouse board since 2026-08-03. Full hiring picture for Anduril Industries.

About this role

As a Staff AI Infrastructure Engineer at Anduril Industries, you will architect and build the machine learning platform that powers autonomous systems. Your role involves designing and maintaining infrastructure for model development, optimizing ML research processes, and managing large datasets. You will collaborate with AI researchers and engineers to ensure robust and efficient ML operations across various environments.

Our read on this posting3.0out of 5
benefits
1/5
freshness
4/5
career value
5/5
role clarity
5/5
pay transparency
0/5

Scored from the posting itself — how clearly the role is described, how much it says about pay and benefits, and how recently it was listed. Not a judgement of Anduril Industries as an employer.

What you need

  • 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.

Nice to have

  • Experience building and running ML infrastructure, model serving, or software registries within secure, air-gapped, or highly regulated environments (e.g., IL5/IL6, GovCloud).
  • Experience specifically building training and evaluation platforms for Large Language Models, Generative AI architectures, or Reinforcement Learning (RL) pipelines.
  • Experience profiling training hardware performance, identifying bottlenecks across networks and memory, and optimizing hardware utilization.
  • Experience designing and operating multi-tenant ML platforms that serve multiple research teams, with robust resource isolation, quota management, and fair scheduling across shared GPU clusters.
  • Hands-on experience with next-generation AI accelerators beyond standard GPUs (e.g., AWS Trainium, Google TPUs, or custom ASICs) for training and inference workloads.

What you get

  • Comprehensive, competitive benefits package available at little to no cost to employees.
  • Highly competitive equity grants included in the majority of full time offers.

Worth weighing

  • No specific mention of the technologies or frameworks used in the existing ML platform, which could impact your familiarity with the stack.
  • The role requires eligibility for a U.S. Top Secret security clearance, which may be a barrier for some candidates.

Summarised from Anduril Industries's posting. Read the full original.

Listed by Anduril Industries on their greenhouse job board, last confirmed open on 2026-09-17. PitchMeAI is not the employer.

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