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Internship

Machine Learning Runtime Engineer – Internship

PEY 2025

Confirmed live in the last 24 hours

Cerebras

Cerebras

201-500 employees

Develops AI acceleration hardware and software

AI & Machine Learning
Financial Services
Healthcare

Toronto, ON, Canada

Category
Applied Machine Learning
Deep Learning
AI & Machine Learning
Required Skills
Python
Data Structures & Algorithms
C/C++
Requirements
  • Currently enrolled in a University in Computer Science, Computer Engineering, or any other related discipline
  • Strong proficiency in C/C++
  • Familiarity with Python or other scripting language
  • The ability to operate at multiple levels of abstraction in the software stack
Responsibilities
  • Be able to understand the flow of data in a distributed system and how to characterize performance pain points
  • Develop algorithms for allocation of compute, communication, and memory resources
  • Measure, analyze, and improve execution of Runtime software (that is responsible for training large models with massive datasets)
  • Integrate successful optimizations into production software stack
  • Implement mathematical models in C++ or Python using discrete optimization techniques and standard libraries and packages

Cerebras Systems focuses on accelerating artificial intelligence (AI) with its CS-2 system, the fastest AI accelerator on the market. This system replaces traditional GPU clusters, simplifying the process of AI computations for clients in various industries, including pharmaceuticals and government research. By providing proprietary hardware and software solutions, Cerebras enables faster AI training and lower latency, which helps reduce costs in AI research and development. The company's goal is to make AI tasks more efficient and accessible across different sectors.

Company Stage

Series F

Total Funding

$720M

Headquarters

Sunnyvale, California

Founded

2016

Growth & Insights
Headcount

6 month growth

10%

1 year growth

19%

2 year growth

-3%
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Simplify's Take

What believers are saying

  • Cerebras' IPO and significant funding, including $720 million raised, position it for substantial growth and market penetration.
  • Collaborations with industry giants and government labs, such as GlaxoSmithKline, AstraZeneca, and Argonne National Lab, validate the effectiveness and demand for Cerebras' technology.
  • The CS-2 system's ability to produce faster results in critical applications like cancer drug response prediction models highlights its transformative potential in healthcare and scientific research.

What critics are saying

  • Competing against established giants like Nvidia poses significant market challenges and could impact Cerebras' market share.
  • The high cost and complexity of developing and maintaining cutting-edge hardware like the WSE-3 chip could strain resources and affect profitability.

What makes Cerebras unique

  • Cerebras' CS-2 system replaces traditional GPU clusters, eliminating complexities in parallel programming and distributed training.
  • The WSE-3 chip, with 40 trillion transistors, is designed to train AI models 10 times larger than current top models like GPT-4, setting a new industry standard.
  • Strategic partnerships with major entities like Dell and Aleph Alpha enhance Cerebras' reach and influence in the AI and high-performance computing markets.

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