Advanced quantization algorithms research and development for complex generative models, including (but not limited to) FlexRound, PrefixQuant, GPTQ, SpinQuant, Automatic mixed precision, and other INT/ FP Quant algorithms.
Experiments and research on generative models training and fine‑tuning, including pre‑training, SFT, PEFT, RL, reasoning, loss‑function design and optimization, as well as quantization‑aware training built on top of advanced quantization methods.
Efficient inference algorithms research and development, e.g. batching, KV caching, efficient attentions, long context, speculative decoding.
Model compression, lossy or lossless, structural and neural search.
Optimization based learning and learning based optimization.
Generative AI Systems prototyping
Apply solutions toward systems innovations for model efficiency advancement on device as well as in the cloud.
Python, Pytorch programmer
Minimum Qualifications
- Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
- OR
- Master's degree in Computer Science, Engineering, Information Systems, or related field and 1+ year of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
- OR
- PhD in Computer Science, Engineering, Information Systems, or related field.
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