Deep Learning Researcher

1 week ago

Toronto, Ontario, Canada STMicroelectronics Full time

OUR STORY
At STMicroelectronics, we believe in the power of technology to drive innovation and make a positive impact on people, businesses, and society. As a global semiconductor company, our advanced technologies and chips form the hidden foundation of the world we live in today.
When you join ST, you will be part of a global business with more than 115 nationalities, present in 40 countries, and comprising over 50,000 diverse and dedicated creators and makers of technology around the world.
Developing technologies takes more than talent: it takes amazing people who understand collaboration and respect. People with passion and the desire to disrupt the status quo, drive innovation, and unlock their own potential.
Embark on a journey with us, where you can innovate for a future that we want to make smarter and greener, in a responsible and sustainable way. Our technology starts with you.
YOUR ROLE
Your role is to work on Research and Development of techniques in the field of
model compression and Neural Architecture Search (NAS)
. You will contribute to cutting-edge work on compression primitives—including
tensor decomposition, quantization, pruning
, and related methods—and will play a central role in developing
zero- or few-shot performance proxies
to enable efficient search and evaluation, with a particular emphasis on
ultra–low-bit quantization
.

  • Lead the development of a novel zero-cost proxy aimed at accurately predicting model behavior under ultra–low-bit quantization.
  • Advance a hardware-aware model compression framework, integrating new techniques into scalable research tools.
  • Conduct rigorous experimental studies, including ablation analyses and hardware benchmarking on diverse accelerators.
  • Propose novel models using these optimization techniques.
  • Prepare and disseminate research outcomes through peer-reviewed publications, technical reports, and conference presentations.

Your Skills & Experiences

  • Current Ph.D. or Master's student in Computer Science, Electrical and Computer Engineering, or a related field.
  • Strong foundational knowledge of deep learning theory, including CNN architectures and optimization.
  • Demonstrated proficiency in Python and experience with PyTorch for model development and experimentation.
  • Prior exposure to model compression techniques (quantization, pruning, decomposition) is advantageous but not required.
  • Solid understanding of the mathematical principles underlying deep learning, such as linear algebra, probability, and numerical optimization.

ST is proud to be one of the 17 companies certified as a 2025 Global Top Employer and the first and only semiconductor company to achieve this distinction. ST was recognized in this ranking thanks to its continuous improvement approach and stands out particularly in the areas of ethics & integrity, purpose & values, organization & change, business strategy, and performance.

At ST, we endeavor to foster a diverse and inclusive workplace, and we do not tolerate discrimination. We aim to recruit and retain a diverse workforce that reflects the societies around us. We strive for equity in career development, career opportunities, and equal remuneration. We encourage candidates who may not meet every single requirement to apply, as we appreciate diverse perspectives and provide opportunities for growth and learning. Diversity, equity, and inclusion (DEI) is woven into our company culture.

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