Spotinst is one the largest and most advanced company for cloud work-load automation. We aim to improve performance, reduce complexity and lower compute infrastructure costs.
As a major participant in the cloud optimization field, Spotinst faces many challenges. Our new research team provides solutions for complex core problems, such as usage prediction and resource allocation, handling large amounts of data. We work closely with the product teams in order to bring state of the art technology to production.
What you’ll do:
- Find and apply suitable neural network architectures, and evaluate them against current state-of-the-art models
- Devise better data-driven models for resource-allocation and usage-prediction under constraints
- Explore existing approaches for time-series prediction, e.g., ARIMA, Prophet
- Make models that can be applied to Spotinst product development
- Lay the foundations for research in a fast growing company
- MSc, or Ph.D. degree in CS, EE or a related field (e.g., machine learning, signal processing, data mining and statistics)
- Publication record in machine learning or related conferences (e.g., NIPS, ICML, ICLR, CVPR, ICCV, ECCV, ACL, NAACL, EMNLP, and others)
- Proven experience in the field of machine learning and deep learning
- Excellent analytical skills
- Strong coding skills in Python
- Familiarity with frameworks for deep learning, e.g., Pytorch, Keras
- Theoretical knowledge in the field of time-series analysis