Responsibilities

• 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)

Minimum qualifications

• 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.

Preferred qualifications

• 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.