Role overview
**What You'll Do**
* Design and develop foundational ML models for CAE applications
* Build data pipelines for training, evaluation, and deployment of ML systems
* Collaborate with full-stack engineers to integrate ML capabilities into our platform
* Help establish ML best practices, experiment tracking, and model governance
* Participate in product strategy discussions and help define our technical ML roadmap
* Contribute to research publications and IP development
**Required Qualifications**
* 5+ years of professional experience in applied machine learning
* Strong expertise in PyTorch for deep learning research and development
* Advanced proficiency with Python for ML model implementation and data processing
* Experience with large language models, multimodal models, and retrieval-augmented generation
* Proven track record of deploying ML models to production environments
* Experience with ML infrastructure and MLOps practices
* Strong background in mathematics, particularly linear algebra, calculus, and statistics
* Demonstrated ability to conduct independent research and solve novel problems
* Strong communication skills and ability to explain complex ML concepts clearly
**Preferred Qualifications**
* PhD or MS in Computer Science, Machine Learning, or related technical field
* Familiarity with reinforcement learning and optimization techniques
* Experience with geometric deep learning or graph neural networks
* Familiarity with CAE software or engineering simulation tools
* Background in physics-informed neural networks or scientific ML
* Experience with high-performance computing for ML
* Publication record at top ML conferences (NeurIPS, ICML, ICLR, etc.)
**What We Offer**
* Competitive salary and equity package
* Opportunity to shape the direction of an innovative product from its inception
* Opportunity to work with cutting-edge AI and engineering technologies
* Opportunity to publish and present at industry conferences
* Direct access to customers and users, seeing your impact firsthand
* Flat organizational structure with transparent decision-making