Full-Time

ML Stack Optimization Engineer

Posted on 12/20/2024

Cerebras

Cerebras

201-500 employees

Develops AI acceleration hardware and software

Data & Analytics
Enterprise Software
AI & Machine Learning

Senior, Expert

Toronto, ON, Canada

Category
Applied Machine Learning
AI & Machine Learning
Required Skills
Python
C/C++
Requirements
  • Master’s degree in Computer Science, Electrical Engineering, or a related field required; Ph.D. preferred.
  • Proficiency in C/C++ programming and experience with low-level optimization.
  • Proficiency in Python programming.
  • Strong background in optimization techniques, particularly those involving NP-hard problems.
  • Familiarity with either of the following is a plus: The Satisfiability Problem, Integer-Linear Programming, Constraint Satisfaction Problems.
  • Familiarity with MLIR is a plus.
  • Excellent problem-solving skills and a strong analytical mindset.
  • Ability to work in a fast-paced, collaborative environment.
Responsibilities
  • Design, develop, and optimize compiler technologies for AI chips using LLVM and MLIR frameworks.
  • Identify and address performance bottlenecks, ensuring optimal resource utilization and execution efficiency.
  • Work with the machine learning team to integrate compiler optimizations with AI frameworks and applications.
  • Contribute to the advancement of compiler technologies by exploring new ideas and approaches.

Cerebras Systems specializes in accelerating artificial intelligence (AI) processes with its CS-2 system, which is designed to replace traditional clusters of graphics processing units (GPUs) used in AI computations. The CS-2 system simplifies the complexities of parallel programming, distributed training, and cluster management, making AI tasks more efficient. Clients from various sectors, including pharmaceuticals, government research labs, healthcare, finance, and energy, utilize the CS-2 to achieve faster results in critical applications like cancer drug response prediction. Cerebras generates revenue by selling its proprietary hardware and software solutions, including the CS-2 systems and associated cloud services. The company's goal is to streamline AI research and development, enabling clients to reduce costs and improve the speed of AI training and inference.

Company Stage

Series F

Total Funding

$700.4M

Headquarters

Sunnyvale, California

Founded

2016

Growth & Insights
Headcount

6 month growth

6%

1 year growth

16%

2 year growth

-1%
Simplify Jobs

Simplify's Take

What believers are saying

  • Collaboration with Dell expands Cerebras' reach in enterprise generative AI projects.
  • The WSE-3 processor attracts clients seeking cutting-edge AI technology.
  • Cerebras' IPO filing suggests potential for increased capital for R&D and expansion.

What critics are saying

  • Reliance on high-profile clients like GlaxoSmithKline poses a risk if they switch.
  • Competition with Nvidia may lead to aggressive pricing and reduced profit margins.
  • Dependency on Dell's distribution channels could influence Cerebras' product positioning.

What makes Cerebras unique

  • Cerebras' WSE-3 chip has 1.4 trillion transistors, surpassing competitors in AI hardware.
  • The CS-2 system replaces traditional GPU clusters, simplifying AI computations significantly.
  • Cerebras' AI inference service offers unmatched performance and cost efficiency in the market.

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