Required Qualifications:
- Doctorate in computer science or relevant field
- OR equivalent experience.
Preferred Qualifications:
- Doctorate in relevant field AND 2+ years related research experience.
OR equivalent experience.
- Experience publishing academic papers as a lead author or essential contributor.
- Experience participating in a top conference in relevant research domain.
- Background in system and architecture, including experience with computer hardware, software, and networking technologies.
- Deep knowledge about the latest large model training/inference technology such as instruction finetuning, Reinforcement Learning (RL) and Reinforcement Learning with Hindsight Experience Replay (RLHF), processed and self-reward modeling, low-precision training/inference, etc.
- A track record of published research in the field of AI or other system innovation is a plus.
- Keen interest in general AI research, including but not limited to large foundation models and artificial specialized intelligence.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: