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ML Engineer, Surrogate Modeling (Vehicle Engineering)

1 hour, 24 minutes ago
United States
Full-time
Junior
Machine Learning Engineer
Software Development
CI/CD Git Linux Machine Learning Python PyTorch Statistics TensorFlow
Apply Now
SpaceX

SpaceX

SpaceX designs, manufactures, and launches advanced rockets and spacecraft with the aim of revolutionizing space technology and enabling human life on other planets.

Aerospace & Defense
10K-50K
Founded 2002
View All Jobs 215

Description

  • Develop, train, evaluate, and deploy production-grade AI surrogate models for engineering simulation workflows.
  • Design and implement state-of-the-art neural architectures and training strategies for complex engineering domains.
  • Build scalable data pipelines to preprocess and manage large volumes of high-fidelity simulation results.
  • Stay current with research in neural operators, physics-informed machine learning, and surrogate modeling, and apply new techniques as needed.
  • Collaborate with hardware, simulation, and domain engineers on architecture, design, and code reviews.
  • Identify high-leverage engineering problems where AI can provide reliable solutions.
  • Develop and apply methods for uncertainty quantification, active learning, and inverse problems such as geometry and shape optimization.
  • Validate AI systems for accuracy, robustness, and reliability in engineering use.

Requirements

  • Bachelor’s degree in computer science, data science, engineering, math, physics, or a related technical discipline, or 4+ years of professional software development experience in lieu of a degree.
  • 1+ years of software development experience in Python for machine learning, AI, or data science applications.
  • Master’s or PhD in computer science, machine learning, engineering, or a related field with a focus on surrogate modeling or AI for scientific/engineering simulation (preferred).
  • Experience training, tuning, and deploying production-grade ML surrogate models in real engineering workflows (preferred).
  • Expert-level understanding of at least one modern architecture class such as Fourier Neural Operators (FNO), neural operators, MeshGraphNet, Transolver, graph neural networks, or physics-informed neural networks (preferred).
  • Experience solving inverse problems such as geometry optimization or design under uncertainty (preferred).
  • Strong understanding of traditional simulation and numerical methods such as CFD, FEA, and thermal analysis, and how to integrate them with surrogate models (preferred).
  • Experience with uncertainty quantification techniques for surrogate models (preferred).
  • Hands-on experience building active learning or adaptive sampling pipelines (preferred).
  • Proficiency with deep learning frameworks such as PyTorch, TensorFlow, or JAX (preferred).
  • Experience with surrogate modeling libraries such as NVIDIA PhysicsNemo or similar (preferred).
  • Experience developing on Linux systems with GPU accelerators (preferred).
  • Strong understanding of software engineering best practices including version control, testing, and continuous integration (preferred).
  • Solid foundation in statistics, numerical methods, and core machine learning algorithms (preferred).
  • Ability to work extended hours and weekends as necessary.

Benefits

  • Pay range of $125,000 to $145,000 per year for AI Software Engineer/Level I, or $145,000 to $175,000 per year for AI Software Engineer/Level II.
  • Potential long-term incentives, including company stock, stock options, or long-term cash awards.
  • Potential discretionary bonuses.
  • Employee Stock Purchase Plan with the ability to buy additional stock at a discount.
  • Comprehensive medical, vision, and dental coverage.
  • 401(k) retirement plan, plus short- and long-term disability insurance and life insurance.
  • Paid parental leave.
  • 3 weeks of paid vacation, 10 or more paid holidays per year, and paid sick leave.

Interested in this position?

Apply directly on the company website

Apply Now

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