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Senior ML Engineer, Core Development

Anduril· Air Dominance & Strike : Air Dominance & Strike Hardware : Aerodynamics & Performance
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Costa Mesa, CA$220k - $292kFull-timePosted 1mo ago

About the role

Senior ML Engineer responsible for owning the surrogate modeling stack for Air Dominance & Strike, applying physics-informed ML to accelerate engineering simulations (CFD, FEA, thermal, aeroelastic) and delivering production-grade models integrated into the design workflow.

Responsibilities

  • Own the Surrogate Modeling Stack: Drive the end-to-end design, training, and deployment of production-grade surrogate models to accelerate critical simulation workflows (CFD, FEA, thermal, structural, and aeroelastic) across air vehicle design.
  • Develop State-of-the-Art Architectures: Design and implement neural architectures tailored to engineering physics, developing new techniques for uncertainty quantification, active learning, and inverse problems (such as geometry and shape optimization).
  • Build Robust Data & Training Infrastructure: Create the pipelines behind the training—extracting, aggregating, and sanitizing tens of thousands of high-fidelity results from solver outputs.
  • Optimize & Integrate: Optimize inference for the design loop (maximizing GPU utilization, batched evaluation, and interactive-speed latency) and seamlessly integrate surrogate predictions into the tooling our domain engineers already use.
  • Collaborate & Mentor: Partner with domain engineers to identify where ML delivers the highest leverage, stay current with Physics AI research, and provide technical mentorship to non ML engineers.

Qualifications

  • BS, MS, or PhD in aerospace, thermal, mechanical, or electrical engineering, or in machine learning/AI/data science with a demonstrated engineering foundation.
  • 3+ years of experience taking ML models from R&D into production using large-scale scientific or engineering datasets.
  • Working knowledge of modern surrogate architectures (e.g. GNNs, Transolver, DoMINO & GeoTransolver) combined with hands-on experience running physical simulations (CFD, FEA, thermal, etc.) and a command of the underlying numerical methods.
  • Proficiency in Python and MATLAB; experience with PyTorch, TensorFlow, and NVIDIA PhysicsNeMo (Modulus); experience developing on Linux with GPU accelerators and distributed training.
  • Track record of building production data pipelines from heterogeneous engineering sources, utilizing uncertainty quantification, conducting statistical analysis, and building data science dashboards
  • Must be a U.S. Person eligible to obtain and maintain a U.S. Top Secret security clearance

Skills

Required:Surrogate modeling / physics-informed MLNeural architectures for engineering physicsData & training infrastructurePython, MATLABPyTorch, TensorFlow, NVIDIA PhysicsNeMoLinux, GPU accelerators, distributed trainingUncertainty quantification, statistical analysisEngineering data pipelines
Nice to have:Visualization tools (Plotly, Seaborn, Matplotlib)ML Ops / orchestration (Docker, Weights & Biases, AWS S3, Lambda, SageMaker)

Benefits

  • Comprehensive, competitive benefits package (health, recovery, and other coverage) available to full-time employees
Last updated Sep 9, 2026. Interested? Apply on the company site.

About Anduril

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