Machine Learning Research Scientist (Quantization):
We are seeking a Machine Learning Research Scientist to join a well-funded ($35M Series A) AI hardware accelerator start-up. We are pushing the boundaries of non-von Neuman architectures in order to create smart AI hardware that is more efficient both in cost and power compared to today's digital hardware.
Within this role, you will be leading heavy deep-learning research working alongside a very bright and innovative team. You will be responsible for developing & benchmarking state-of-the-art training methods to adapt our hardware for optimal performance.
We are looking for a Machine Learning Research Scientist with a Ph.D. in Computer Science, Electrical Engineering, or a related field. This person will have a history of multiple relative (sparsity, quantization, deep learning, neural network compression, etc.) publications in top ML conferences. Expertise in DL architectures, training algorithms & strong coding skills is required.
What we can offer an ML Research Scientist:
- Competitive base + Salary + Equity
- Fully remote works anywhere in the US
- Strong benefits
Keywords: Quantization, Optimization, Pruning, Machine Learning, Research Scientist, Pytorch, TensorFlow, Neural Networks, Hardware, Algorithms, Transformers, ResNets, DLRMs, MLP-mixers, backpropagation, SGD, second-order methods, GPU, Caffe, Accelerator, Acceleration, OpenVINO