AI/ML Engineer (Level based on experience)
Palo Alto, CA, United States
About The Role
At Cosmon, you’ll shape the future of computer-aided engineering by building AI that thinks like an 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 — helping customers iterate faster, diagnose failures earlier, and bring better products to market.
This is a rare chance to join early and make a foundational impact at a company reimagining CAE for the AI era.
To apply, email us at info (at) cosmon (dot) com
Key Responsibilities
Research, design, and develop AI/ML algorithms to tackle complex challenges in computer-aided engineering, simulation, and design automation.
Build scalable AI solutions and collaborate with cross-functional teams to integrate models seamlessly into existing CAE workflows and infrastructure.
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.
Requirements
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.
Strong Plus
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.
