Cerebras’ fully-integrated system is built from the ground up with a singular focus on AI.
To explore new techniques and algorithms at the frontier of machine learning uniquely enabled by our revolutionary technology, our experienced team of Machine Learning engineers and researchers work in collaboration with other experts in the company, giving insight and access to every level of our system stack.
This is an applied research position with a focus on working with state-of-the-art research and developing novel models and algorithms on top of our core technology. We are interested in a wide range of machine learning algorithms and application domains with a focus on exploring new ideas that hold the potential to substantially reduce computational constraints limiting today’s machine learning research.
- Develop algorithms for training and inference in sparse neural networks
- Develop novel optimizers and learning algorithms such as local learning rules and layer-parallel training
- Develop novel network architectures and layers such as, normalization, activation functions and parameter layers
- Publish and present research at leading machine learning conferences
Skills and qualifications:
- Experience with machine learning frameworks, such as TensorFlow, Caffe/2 and PyTorch.
- Fluency in a programming language, such as Python, C.
- Strong grasp of linear algebra and statistics
- Strong track record of relevant research success in roles at the level of doctoral, postdoctoral in academia or in industrial R&D.
- Strong track record of relevant publications / patents.