AI/ML Engineer

As an AI/ML Engineer, you’ll design, train, and deploy models that accelerate simulation, improve accuracy, and unlock entirely new ways of exploring the design space. From adaptive solvers and reduced-order modeling to generative design and real-time validation, your work will push the boundaries of what CAE can achieve.

You’ll work alongside experts in engineering and applied AI to integrate machine learning directly into high-fidelity simulation pipelines that helping customers iterate faster, diagnose failures earlier, and bring better products to market

• Research, design, and develop AI/ML algorithms to tackle complex challenges in computer-aided engineering, simulation, and design automation.
• Lead performance improvements, from optimizing model accuracy to analyzing outputs and addressing system-level bottlenecks.
• Stay at the forefront of AI and simulation research, bringing the latest advances in ML, generative design, and physics-informed modeling into production-ready tools.
• Build and optimize solutions such as adaptive solvers, reduced-order models, generative design systems, and real-time validation tools.
• Integrate machine learning models directly into high-fidelity engineering simulation pipelines.
• Enable faster failure detection and diagnosis through intelligent data-driven models.
• Contribute to advancing next-generation CAE capabilities powered by AI.
• Participate in building foundational AI systems that redefine how engineering simulations are performed.
  
  

The role requires 5+ years of experience building and deploying AI/ML models in applied engineering or scientific domains, along with 2+ years of technical leadership taking projects from research to production.

• 5+ years of experience developing and deploying AI/ML models with a proven track record of delivering impact in applied engineering or scientific domains.
• 2+ years of technical leadership guiding AI/ML projects from research to production.
• Proficiency in Python and modern AI/ML frameworks (e.g., PyTorch, JAX, TensorFlow).
• Experience with AI/ML algorithms for sequential, spatial, or physics-informed data (e.g., time series, text, mesh, or simulation outputs).
• Familiarity with MLOps practices and building AI/ML systems end-to-end, from prototyping to scalable deployment.
• Strong communication skills and ability to collaborate across software engineers, CAE specialists, and applied scientists in a distributed, interdisciplinary environment.
  
  

A strong plus for this role includes experience in CAE, physics-based simulation, or engineering design tools, along with exposure to NLP, LLMs, and agentic AI systems applied in technical or engineering domains.

• Experience in CAE, physics-based simulation, or engineering design tools.
• Experience with NLP, LLMs, and agentic AI systems applied to technical domains.
• Experience working in a fast-paced startup or research-driven environment.