Discrete Optimization Engineer

Cerebras is developing 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 the deep learning workload.

Cerebras is building a team of exceptional people to work together on big problems. Join us!

The Team

The Place & Route team designs a backend system that transforms an abstract computational graph to a specific plan that can be run on our hardware. Our team consists of highly skilled PhDs and engineers with strong backgrounds in parallel computing, graph algorithms, constrained optimization, and machine learning, with many combined years of industry experience. We are looking to grow our team with highly motivated individuals eager to solve challenging algorithmic problems and implement their methods, following sound engineering principles.

The Role

As a Discrete Optimization Engineer, you will directly impact the performance at which deep learning models are executed on hardware and be responsible for enabling next-generation AI applications that require substantial computational capabilities. In this position, you will develop model and implement various optimization problems in the software stack.

Specific responsibilities may include:

  • Develop mathematical models for optimizations needed in various stages of software stack
  • Implement mathematical models in C++ or Python using discreate optimization techniques and standard libraries and packages.
  • Measure, analyze, and optimize quality of results produced mathematical models and their implementations.

Skills & Qualifications

  • PhD or Master degree in Computer Science, Applied Mathematics, or related field.
  • Expert knowledge of linear programming, constraint solvers, and combinatorial optimization
  • Strong proficiency in C/C++ or other language for designing large, performant systems.
  • Familiarity with Python or other scripting language.
  • The ability to operate at multiple levels of abstraction.

Successful candidates need to have demonstrated the ability to both solve challenging algorithmic problems and implement them cleanly in performant code.

Location

  • Our cozy and well-appointed headquarters are in the heart of Silicon Valley near downtown Los Altos, California.

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