ML Developer - Software Automation & Developer Infrastructure Intern (PEY 2025)

Posted 4 Days Ago
Be an Early Applicant
Toronto, ON
Internship
Artificial Intelligence
The Role
As an ML Developer Intern, you will focus on automating testing, improving software design, and enhancing product quality through developing verification tests and tools. You will identify software weaknesses and contribute to ensuring high-quality deliverables, impacting HW-based deep learning accelerators.
Summary Generated by Built In

Cerebras has developed a radically new chip and system to dramatically accelerate deep learning applications. Our system runs training and inference workloads orders of magnitude faster than contemporary machines, fundamentally changing the way ML researchers work and pursue AI innovation.

We are innovating at every level of the stack – from chip, to microcode, to power delivery and cooling, to new algorithms and network architectures at the cutting edge of ML research. Our fully-integrated system delivers unprecedented performance because it is built from the ground up for deep learning workloads.
Cerebras is building a team of exceptional people to work together on big problems. Join us!

About The Role:
As a Machine Developer - Software Automation & Developer Infrastructure Engineer, you will use your knowledge of testing and testability to influence better software design, promote proper engineering practice, bug prevention strategies, testability, scalability, and other advanced quality concepts. The position will play a huge role in the quality of Cerebras software. We are looking for engineers that have a broad set of technical skills and who are ready to tackle the biggest at-scale problems in HW-based deep learning accelerators.
Responsibilities:

  • Write scripts to automate testing and create tools to allow easy development of software regression tests
  • Help identify weak spots and potential customer pain points and drive the software organization towards customer focused quality metrics
  • Implement creative ways to break software and identify potential problems
  • Contribute to developing requirements specifications with a focus on developing verification tests

Requirements:

  • Enrolled within University of Toronto's PEY program with a degree in Computer Science, Computer Engineering, or any other related discipline
  • Experience in developing automated tests for compute/machine learning or networking systems within a large-scale enterprise environment
  • Ability to take responsibility for monitoring product development and usage at all levels with an end goal toward improving product quality
  • Strong knowledge of software system design, C++ and Python

Preferred:

  • Strong software testing experience with a proven track record in scaling highly technical teams
  • Knowledge of UNIX/Linux and Windows environments
  • Knowledge of neural network architecture and ML/AI deep learning principles
  • Prior experience in designing and developing test automation for HW systems involving ASICs or FPGAs
  • Prior experience working with live hardware systems and debug tools operating in a real time environment such as networking devices or live computing systems


Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.

This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.

Top Skills

C++
Python
The Company
HQ: Sunnyvale, CA
402 Employees
On-site Workplace
Year Founded: 2016

What We Do

Cerebras Systems is a team of pioneering computer architects, computer scientists, deep learning researchers, functional business experts and engineers of all types. We have come together to build a new class of computer to accelerate artificial intelligence work by three orders of magnitude beyond the current state of the art.

The CS-2 is the fastest AI computer in existence. It contains a collection of industry firsts, including the Cerebras Wafer Scale Engine (WSE-2). The WSE-2 is the largest chip ever built. It contains 2.6 trillion transistors and covers more than 46,225 square millimeters of silicon. The largest graphics processor on the market has 54 billion transistors and covers 815 square millimeters. In artificial intelligence work, large chips process information more quickly producing answers in less time. As a result, neural networks that in the past took months to train, can now train in minutes on the Cerebras CS-2 powered by the WSE-2.

Join us: https://cerebras.net/careers/

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