AI/ML Engineer
Role details
Job location
Tech stack
Job description
Join an early-stage, venture-backed AI startup reimagining computer-aided engineering (CAE) for the AI era. As an AI/ML Engineer, you'll shape the future of engineering automation by building AI that thinks like an engineer - designing, training, and deploying 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 collaborate closely with experts in applied AI and mechanical engineering, integrating machine learning directly into high-fidelity simulation pipelines to help customers iterate faster, diagnose failures earlier, and bring better products to market. This is a rare opportunity to join early and make a foundational impact., * Research, design, and develop AI/ML algorithms to tackle complex challenges in simulation, design automation, and computer-aided engineering.
- 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.
- Guide AI/ML projects from research through to production deployment.
- Contribute to MLOps practices and help build robust, end-to-end AI/ML systems.
Requirements
Do you have experience in System deployment?, * 4+ 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, mesh data, or simulation outputs).
- Familiarity with MLOps practices and building AI/ML systems end-to-end, from prototyping to scalable deployment.
- Strong understanding of engineering principles in simulation, modeling, and optimization.
- Bachelor's or advanced degree in Computer Science, Mechanical Engineering, Electrical Engineering, or a related field.
Nice to Have:
- Experience with CAE, CAD, and/or PLM tools (e.g., Ansys, Abaqus, COMSOL, SolidWorks, NX).
- Experience in a fast-paced startup environment.