8 months ago
Machine Learning Scientist (Deep Learning, Graph Theory, Matrix Multiplication)
We are a Boston-based MIT spinout who are tackling an industry-wide problem within computer processing. From our research, we believe that our specific technology will bypass the limits of next-gen CPUs using a different approach to processing Deep Neural Networks. Currently, we are 40 people strong and are soon to be entering a rapid stage of growth, as we recently raised over $40 million dollars in our Series A from leading US VCs.
We are looking to add another Machine Learning Scientist (Deep Learning) to our team who will help drive our research in Deep Learning and Neural Networks. As a Machine Learning Scientist, you will be part of a small growing team (from top academic backgrounds) all working on surpassing the limitations of what is possible with responsible Machine Learning. If you have a passion for solving challenging technical problems and working on an area of technology which has never been attempted before - you will enjoy the work that we have for you here.
As a Machine Learning Scientist, it is not at all necessary for you to have come from a hardware background. The ideal candidate will have come from a Computer Science/Engineering, Physics or Mathematics background and has published relevant papers in the top machine learning conferences (ICML, NeurIPS, ECML etc). We are interested if you have applied experience or even if you are completely from a theoretical background in Machine Learning.
What we can offer a Machine Learning Scientist
- An opportunity to work with our collaborative research team on novel work that will revolutionize modern-day computing as we know it.
- A culture of openness and collaboration - we are all working together under a shared vision.
- A great location in downtown Boston
- Excellent benefits.
Key Skills include: Deep Learning Scientist, Machine Learning Scientist, Machine Learning Engineer, TensorFlow, PyTorch, Keras, C++, Python, Deep Neural Networks, LSTMs, CNNs, NeurIPS, ICML, ECML, ICLR, JMLR.