Senior ML Engineer, Core Development

Anduril Industries; Costa Mesa (CA); On-site; USD 220,000 - 292,000; Full time

Benefits offered by this job

Equity grants

Comprehensive benefits

Competitive compensation

Job summary

Anduril Industries in Costa Mesa, CA is seeking a Machine Learning Engineer to apply PhysicsML to accelerate physics simulations for air dominance and strike programs. You will own the surrogate modeling stack and collaborate with aerodynamicists, structures and thermal engineers.

You will train, deploy surrogate models, design neural architectures, build data pipelines, optimize inference, and mentor non-ML engineers while pursuing advanced physics-aware ML research.

Qualifications

• BS, MS, or PhD in aerospace, thermal, mechanical, electrical engineering, or in ML/AI with engineering foundation.
• 3+ years of ML production experience on large-scale engineering data.
• PhysicsML expertise with surrogate architectures and CFD/FEA/thermal experience.
• Proficiency in Python and MATLAB; PyTorch, TensorFlow; NVIDIA NeMo/Modulus.
• Experience with Linux, GPU accelerators, distributed training.
• Clearance: U.S. Person eligible for Top Secret clearance.

Responsibilities

• Own the Surrogate Modeling Stack: end-to-end design, training, and deployment of production surrogate models for CFD, FEA, thermal, and aeroelastic workflows.
• Develop state-of-the-art neural architectures for engineering physics, including uncertainty quantification and active learning for inverse problems.
• Build robust data and training pipelines to extract and sanitize large solver outputs.
• Optimize inference for design loops and integrate predictions into existing tooling used by engineers.
• Collaborate with domain engineers and mentor non-ML staff, staying current with PhysicsAI research.

Skills

PhysicsML

Surrogate models

Python

MATLAB

PyTorch

TensorFlow

NVIDIA NeMo (Modulus)

GNNs

Transolver

GeoTransolver

Uncertainty quantification

Active learning

Inverse problems

GPU acceleration

Distributed training

U.S. Top Secret clearance

Education

BS/MS/PhD in aerospace, thermal, mechanical, or electrical engineering, or in ML/AI/data science with an engineering foundation

Tools

Python

MATLAB

PyTorch

TensorFlow

NVIDIA PhysX NeMo (Modulus)

Linux

Docker

Weights & Biases

AWS S3

Lambda

SageMaker

Job description

Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.

Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing theexpertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed,builtand sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into arealtime, 3Dcommandand control center. As the world enters an era of strategic competition, Anduril is committed to bringingcutting-edgeautonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.

About the Team:
Air Dominance & Strike designs, builds, and flies autonomous air vehicles—from collaborative combataircraftto expendable cruise missiles and counter-UAS interceptors. Our vehicles move from whiteboard to first flight on timelines that traditional primes consider impossible, which means our design cycles live or die on how fast we can close the iteration loop. The Anduril AIEngineering team exists to collapse that loop.

We are engineers first. We work from engineering first principles and unlock capability through machine learningand AI. We are building to scale across CFD, FEA, thermal, and electromagnetics, with pipelines, architectures, and validation practices that carry across programs.

About the Job
We are looking for a Machine Learning Engineer to apply the latest research in physicsML to the toughest bottlenecks in our design cycle. This role owns the entire surrogate modeling stack for Air Dominance & Strike—the architectures, the training infrastructure, the simulation data pipelines that feed it, and the tooling design engineers use to consume predictions.

You will develop, train, and deploy surrogate models that accelerate the physics simulations underpinning our air vehicle programs. Working alongside aerodynamicists, structures engineers, and thermal engineers, your models will directly inform decisions on hardware thatactually flies. Where current methods fall short, you will develop new ones, with ample room toidentifynovel applications of physicsML across our portfolio.

Defense experience is notrequired. We are looking for engineers who came to machine learning through the complex physical problems they were already trying to solve.

This role is basedonsitein our Costa Mesa, CA office.

What You’ll Do

• 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: Optimizeinference for the design loop (maximizing GPUutilization, 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 toidentifywhere ML delivers the highest leverage, stay current withPhysicsAI research, and provide technical mentorship tonon MLengineers.

Qualifications

• Education: BS, MS, or PhD in aerospace,thermal,mechanical, or electrical engineering, or in machine learning/AI/data science with a demonstrated engineering foundation.
• Experience: 3+ years of experience taking ML models from R&D into production using large-scale scientific or engineering datasets.
• PhysicsML Expertise: 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.
• Software & Frameworks: Proficiencyin Python and MATLAB; experience withPyTorch, TensorFlow,and NVIDIAPhysicsNeMo(Modulus); and experience developing on Linux with GPU accelerators and distributed training.
• Data & Engineering Best Practices: Track record of building production data pipelines from heterogeneous engineering sources,utilizinguncertainty quantification, conducting statistical analysis, and building data science dashboards
• Clearance: Must be a U.S. Person eligible to obtain andmaintaina U.S.TopSecret security clearance

Preferred Qualifications

• Advanced PhysicsML: Graduate research focused on AI for scientific simulation, experience solving inverse problems (geometry optimization/design under uncertainty), and hands-on experience building active learning or adaptive sampling pipelines.
• Domain Expertise: Prior work in aerospace, automotive, turbomachinery, or another simulation-heavy hardware domain, with familiarity in commercial solvers, meshing tools, and CAD interoperability.
• Advanced Tooling: Working knowledge of foundational ML methods (Gaussian processes,XGBoost,ElasticNetregression& clustering)with the ability to build custom architectures, advanced skills in visualization software (Plotly, Seaborn, Matplotlib), and ML Opsorchestrationexperience (e.g.Docker, Weights & Biases, AWSS3, Lambda&SageMaker)

US Salary Range

$220,000—$292,000 USD

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 Anduril’s total compensation package. Additionally, Anduril offers top-tier benefits for full-time employees, including:

Benefits

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