- Research DNN models
- Develop new architecture search methods (RL, evolution, DARTS)
- Optimize systems with Reinforcement Learning (e.g., Chip Placements, Resource Allocation)
- Accelerate DNN models (e.g., Quantization)
- Bachelor's degree in Computer Science, similar technical field of study, or equivalent practical experience.
- Experience in programming in one or more general-purpose programming languages including but not limited to: Rust, Scala, C++, Java, C, and Python.
- Experience in machine learning frameworks including PyTorch and TensorFlow.
- Master’s or Ph.D. degree in Engineering, Computer Science, or other technically related fields.
- Experience in a wide variety of projects utilizing artificial intelligence, and machine learning technologies.
- Excellent written and verbal communication skills.
Contact & Application