Collaborate on research projects in generative AI and reinforcement learning, design experiments, create datasets, and contribute to publications.
Our mission is to enable hardware deployment at the speed of software development. We are working towards automatic code transpilation and optimization for any hardware application.
In this role, you will collaborate with a small team of talented researchers on ambitious, greenfield projects in generative AI and reinforcement learning.
Core responsibilities:- Design, execute, and analyze experiments with a high degree of independence
- Contribute to core models and frameworks
- Create high-quality datasets (both in-the-wild and synthetic)
- Perform literature reviews and implement new techniques from papers
- Contribute to publications, present at conferences and workshops, etc.
An incomplete list of current and near-term research directions:
- Contrastive representation learning
- Steerability and guided decoding
- Tractable probability models
- Code-specific architectures
- LLM fine-tuning, post-training, RLHF
Requirements
- Ph.D. in Computer Science or a closely related field
- Prior LLM research experience
- Comfortable programming in Python and familiar with frameworks such as PyTorch and HuggingFace
- Publications at peer-reviewed conferences such as NeurIPS, ICLR, ICML, etc.
- Experience with large-scale LLM training, particularly in a distributed computing environment
Benefits
- Competitive salary
- Health care plan (medical, dental, and vision)
- Retirement plan (401k, IRA) with employer matching
- Unlimited PTO
- Flexible hybrid work arrangement
- Relocation assistance for qualifying employees
Top Skills
Huggingface
Python
PyTorch
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