Senior ML Engineer, Core Development
Anduril Industries · Costa Mesa, California, United States
About this role
**Anduril Industries — Senior ML Engineer, Core Development** ## About Anduril Anduril is a defense technology company on a mission to transform U.S. and allied military capabilities with advanced technology. Anduril’s systems are powered by **Lattice OS**, an AI-powered operating system that turns thousands of data streams into a **real-time, 3D command and control** center. The company is focused on delivering **autonomy, AI, computer vision, sensor fusion, and networking** to the military in **months, not years**. ## About the Team **Air Dominance & Strike** designs, builds, and flies autonomous air vehicles—from collaborative combat aircraft to expendable cruise missiles and counter-UAS interceptors. The team moves from whiteboard to first flight on aggressive timelines, and the **AI Engineering team** exists to **collapse the iteration loop**. ## About the Job Anduril is looking for a **Machine Learning Engineer** to apply the latest research in **physics ML** to the toughest bottlenecks in the design cycle. This role owns the **entire surrogate modeling stack** for Air Dominance & Strike, including: - **Architectures** - **Training infrastructure** - **Simulation data pipelines** - **Tooling** engineers use to consume predictions You will develop, train, and deploy **surrogate models** that accelerate the physics simulations underpinning air vehicle programs. You’ll work alongside aerodynamicists, structures engineers, and thermal engineers to inform decisions on hardware that actually flies. Where current methods fall short, you’ll develop new approaches and identify novel applications of physics ML across the portfolio. **Defense experience is not required**—they’re looking for engineers who came to ML through complex physical problems they were already solving. **Location:** Onsite in **Costa Mesa, CA**. ## What You’ll Do - **Own the Surrogate Modeling Stack:** Drive 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, including new techniques for **uncertainty quantification**, **active learning**, and **inverse problems** (e.g., geometry and shape optimization). *(Note: The provided job description appears truncated after the second bullet.)*
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