Machine Learning Research Engineer (LLMs & AI Systems)
TenstorrentDeepTech company
Boston, United StatesMid
Samsung Securities
AFW Partners
Bezos Expeditions
Fidelity Management & Research Co.
LG Electronics
Export Development Canada
Data & AI
About the role
TL;DR
Develop and optimize large language models on custom AI accelerators.
- •Tenstorrent is building next-generation AI systems that push the boundaries of model training, inference, and large-scale distributed compute.
- •The ML Models team sits at the intersection of cutting-edge AI research and high-performance hardware, bringing state-of-the-art machine learning models to life on Tenstorrent’s custom AI accelerators.
- •Key Responsibilities Lead research and development efforts focused on LLM training and inference optimization.
- •Train, evaluate, and optimize state-of-the-art AI models on Tenstorrent hardware.
- •Improve performance through techniques such as speculative decoding, quantization, kernel fusion, flash attention, and distributed training.
- •Requirements Strong Python and PyTorch experience developing and training deep learning models.
- •Deep understanding of ML architectures, LLM training, and inference optimization.
- •Hands-on experience training large-scale machine learning models. 4+ years of industry and/or academic experience in ML research and LLM development.
- •PhD, published research, or experience with speculative decoding is highly valued.
Required skills
PythonPyTorchLLMs
Domain expertise
ai
Tech stack
PythonPyTorch