Machine Learning Scientist

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!

The Role

This is an applied research and engineering position with focus on machine learning algorithm development and distributed computation. As Machine Learning Scientist, you will work with state-of-the-art research and commercial machine learning algorithms and apply them to our core technology. Representative work:

  • Understand and be able to distill, explain state-of-the-art research in machine learning.
  • Develop and implement software for novel machine learning techniques on our system.
  • Decompose machine learning algorithms/models into their computational characteristics.
  • Conduct and report on detailed analysis of machine learning models as executed by the Cerebras platform.
  • Algorithm implementation in the areas of graph transforms, linear algebra kernels, and combinatorial optimization.

Skills & Qualifications

  • Experience with at least two machine learning frameworks, such as TensorFlow, Caffe/2, Torch, Theano.
  • Fluency in at least two programming languages, such as Python, C, bash.
  • Proficiency with linear algebra and dynamical systems.
  • Experience with software development engineering.
  • Experience with both asymptotic performance analysis and performance tuning specific case studies.
  • Candidates with Ph.D. and candidates with B.Sc. are encouraged to apply.

Location

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

Our beautiful San Diego offices overlook views of the Sorrento Valley canyon.

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