Machine Learning Research Scientist at Fathom Computing
Palo Alto, California, United States
🇺🇸 (Posted Jun 5 2018)
About the company
Fathom Computing builds advanced optical technology that replaces electricity in processors with light allowing super-parallel operations. Our brain-scale optical processors will allow us to train vast neural networks with unprecedented performance.
Fathom Computing is building hardware for the future of machine intelligence. Our optical computer will allow training of neural networks with unprecedented performance.
We’re seeking a talented Machine Learning Research Scientist with strong first-principles understanding of neural networks to collaborate with our optics and electronics teams in design and implementation.
While at Fathom, you'll work on:
Implementing novel machine learning algorithms on our unique hardware
Considering several layers of abstraction, all the way from lower level circuits through instruction set architecture
Designing new ML algorithms for future hardware systems
Developing, adapting, and mapping general machine learning algorithms based on features of our hardware
Inventing new models that combine unsupervised and supervised learning, with the kind of creativity usually reserved for blue-sky research projects
Skills & requirements
BS/MS/PhD, or equivalent experience in CS, EE, or related fields (e.g. statistics, applied math, computational neuroscience)
Deep passion and fundamental understanding of design, algorithms, and data structures in modern machine learning and AI
Strong understanding of the fundamentals of neural networks and common general algorithms including RNN, CNN, RL
Strong analytical skills (probability, optimization, etc.)
Experience working with large models
Depth and breadth of knowledge in the field, including recent research results
Knowledge of current frameworks (e.g. TensorFlow, PyTorch, etc.)
Excellent communication skills and ability to collaborate on a complex cross-disciplinary system
Drive to build something that hasn't been built before
You'll do well here if...
You enjoy thoughtful discussions fueled by problem-solving and logic
You're comfortable both leading and contributing individually
You're excited about the future of ML hardware
You enjoy teaching and learning from an interdisciplinary team
Instructions how to apply
see the website
[ job website
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