We are looking for a AI/ML Research Scientist to join our team. In this role, you will drive innovative research at the intersection of artificial intelligence and semiconductor design, developing novel machine learning approaches to solve complex optimization challenges. You will work closely with world-class engineers and researchers to transform cutting-edge ideas into practical solutions that improve chip performance, efficiency, and scalability.
Responsibilities:
- Conduct cutting-edge research in applying machine learning techniques to chip design and optimization problems
- Develop and implement algorithms using graph neural networks, diffusion models, and other advanced ML architectures
- Collaborate with cross-functional teams including engineers and researchers
- Publish research findings in top-tier conferences and journals
- Prototype and validate new approaches using modern ML frameworks
- Contribute to open-source or commercial EDA tools
Must have skills:
- PhD with 1+ years of research experience in Electrical Engineering, Computer Science, Information Systems, or STEM-related field
- 1+ years of experience with modern machine learning architectures including Transformers, Graph Neural Networks, and Diffusion models
- Strong coding skills in Python and C++
- Experience with machine learning frameworks like PyTorch
- At least 1 publication in top machine learning conferences (NeurIPS, ICML, ICLR, etc.)
Nice to have:
- Experience with deep learning on graphs (general graphs, circuit graphs, molecular graphs, or trees)
- Familiarity with classical search and optimization techniques (Genetic Algorithms, Monte-Carlo Tree Search, Dijkstra's Algorithm, etc.)
- Experience with EDA tools, either commercial or open-source
- Publications in top-tier venues focusing on AI for chip design or AI for materials science