Research Associate at HHL Leipzig Graduate School focusing on economic psychology and leadership. Engaging in research projects while supporting teaching and supervising students' theses.
About the role
- Deep Learning Research Scientist at NVIDIA focusing on efficiency innovations for AI technologies. Collaborating across the company to enhance deep learning models and architectures.
Responsibilities
- Research of low-bit number representations and pruning and their effect on neural network inference and training accuracy.
- Innovate with new algorithms to make deep learning more efficient while retaining accuracy, and open-source or publish these algorithms for the world to use.
- Run large-scale deep learning experiments to prove out ideas and analyze the effects of efficiency improvements.
- Collaborate across the company with teams making the hardware, software and deep learning architectures.
Requirements
- PhD degree in AI, computer science, computer engineering, math or a related field or equivalent experience in some of the areas listed below can substitute for an advanced degree.
- 5+ years of relevant industrial research experience.
- Familiarity with state-of-art neural network architectures, optimizers and LLM training.
- Experience with modern DL training frameworks and/or inference engines.
- Fluency in Python, and solid coding/software-engineering practices
- A proven track-record in publications and/or the ability to run large-scale experiments.
- A strong interest in neural network efficiency
Benefits
- Eligible for equity
- Benefits
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