About the Position
As an AI/ML Engineer, you’ll design, develop, and deploy machine learning models that accelerate engineering simulations, improve accuracy, and unlock new possibilities in design exploration. From adaptive solvers and reduced-order modeling to generative design and real-time validation, your work will help push the boundaries of what computer-aided engineering (CAE) can achieve.
You’ll collaborate with experts in engineering and applied AI to integrate machine learning directly into high-fidelity simulation pipelines, helping customers iterate faster, identify and diagnose failures earlier, and bring better products to market.
Job Responsibilities
- Research, design, and develop AI/ML algorithms to solve complex challenges in computer-aided engineering, simulation, and design automation.
- Lead model and system performance improvements, including optimizing accuracy, analyzing outputs, and addressing system-level bottlenecks.
- Stay current with advances in AI and simulation research, bringing emerging techniques in machine learning, generative design, and physics-informed modeling into production-ready solutions.
- Build and optimize AI-powered solutions such as adaptive solvers, reduced-order models, generative design systems, and real-time validation tools.
- Integrate machine learning models into high-fidelity engineering simulation pipelines.
- Develop intelligent, data-driven models that enable faster failure detection, prediction, and diagnosis.
- Contribute to the development of next-generation CAE capabilities powered by AI.
- Help build foundational AI systems that transform how engineering simulations are designed, executed, and analyzed.
Requirements
This role requires 5+ years of experience developing and deploying AI/ML models in applied engineering or scientific domains, along with 2+ years of technical leadership experience taking projects from research and prototyping through production.
- 5+ years of experience developing and deploying AI/ML models, with a proven track record of delivering measurable impact in applied engineering or scientific domains.
- 2+ years of technical leadership experience guiding AI/ML projects from research to production.
- Strong proficiency in Python and modern AI/ML frameworks such as PyTorch, JAX, or TensorFlow.
- Experience developing AI/ML solutions for sequential, spatial, or physics-informed data, including time series, text, meshes, or simulation outputs.
- Familiarity with MLOps practices and experience building AI/ML systems end-to-end, from prototyping through scalable production deployment.
- Excellent communication and collaboration skills, with the ability to work effectively with software engineers, CAE specialists, and applied scientists in a distributed, interdisciplinary environment.
Strong Plus
The following experience will be highly valued:
- Experience with CAE, physics-based simulation, or engineering design tools.
- Experience with NLP, LLMs, and agentic AI systems applied to technical or engineering domains.
- Experience working in a fast-paced startup or research-driven environment.