INTERNSHIP DETAILS

Machine Learning Engineer Intern (PEY)

CompanyTenstorrent University Jobs
LocationToronto
Work ModeOn Site
PostedFebruary 18, 2026
Internship Information
Core Responsibilities
The intern will analyze how ML models compile and run on custom Tenstorrent hardware, focusing on improving kernels for computation and data movement. Responsibilities also include running experiments to evaluate and improve performance across devices and supporting benchmarking and robustness testing.
Internship Type
full time
Company Size
1115
Visa Sponsorship
No
Language
English
Working Hours
40 hours
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About The Company
Tenstorrent is a next-generation computing company that builds computers for AI. Headquartered in the U.S. with offices in Austin, Texas, and Silicon Valley, and global offices in Toronto, Belgrade, Seoul, Tokyo, and Bangalore, Tenstorrent brings together experts in the field of computer architecture, ASIC design, RISC-V technology, advanced systems, and neural network compilers. Tenstorrent is backed by Eclipse Ventures and Real Ventures, Archerman Capital, Samsung Catalyst Fund, and Hyundai Motor Group among others. Join us: www.tenstorrent.com/careers.
About the Role

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities.

Work at the intersection of ML, systems, and hardware. As a Machine Learning Engineer Intern at Tenstorrent, you'll help bring state-of-the-art models like LLMs and CNNs to life on custom AI hardware. You’ll collaborate with experts across software, compiler, and silicon teams while optimizing real workloads for real performance.

This role is on-site, based out of Toronto.

 

Who You Are

  • Enrolled in a CS, CE, or EE program with strong fundamentals.
  • Familiar with ML models and frameworks like PyTorch or TensorFlow.
  • Comfortable programming in Python, C++, or CUDA.
  • Curious about hardware and motivated by performance challenges.

What We Need

  • Analyze how ML models compile and run on Tenstorrent hardware.
  • Improve kernels for computation and data movement.
  • Run experiments to evaluate and improve performance across devices.
  • Support benchmarking, CI pipelines, and robustness testing.

What You Will Learn

  • End-to-end model deployment on custom AI silicon.
  • Compiler flows and kernel-level performance optimization.
  • How to validate, benchmark, and productionize ML models.
  • Cross-functional teamwork with compiler, hardware, and research teams.

 

Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.

This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology. Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2). These requirements apply to persons located in the U.S. and all countries outside the U.S. As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency. If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.

Key Skills
Machine LearningPyTorchTensorFlowPythonC++CUDARISC-VCompilerHardwareLLMsCNNsKernel OptimizationBenchmarkingCI PipelinesSystemsSemiconductors
Categories
EngineeringTechnologyData & AnalyticsSoftwareScience & Research