Sr. Staff Machine Learning Researcher - Model Training & Optimization

Tenstorrent•Toronto, ON

3d•$100,000 - $500,000•Hybrid

About The Position

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. From training large language models to optimizing inference performance at scale, this team works across the full stack to turn breakthrough research into production-ready AI systems. If you are passionate about model training, ML systems optimization, and advancing the frontier of AI research, this is an opportunity to shape how future AI models are developed and deployed.

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.

Nice To Haves

PhD, published research, or experience with speculative decoding is highly valued.

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.
Investigate system bottlenecks and collaborate cross-functionally to drive performance improvements.
Translate cutting-edge ML research into scalable, production-ready solutions.