Cinnamon AI Taiwan Inc. 是一間來自日本的AI新創公司！總部位於日本東京，並在美國、台灣、越南等地設有營業據點或研發中心，員工總計約160人，AI方面的專業人才超過80位！目標在2022年擴展到500位AI專業人才，成為「世界第一的商用AI公司」。
Cinnamon AI Taiwan Inc. 同時是日本Sony投資的第一間AI新創公司，也被Forbes雜誌選為2018年25個值得觀察的Machine Learning新創公司！更在今年1月完成B輪融資募得約1500萬美元的資金。
As a critical role in Science’s success, we are looking to hire Researchers to join our team. The position will work closely to architect efficient APIs and data pipelines around our predictive algorithms. Having an understanding of key Machine Learning concepts as well as a strong software background makes the Cinnamon a linchpin of our AI-First software team.
This is an exciting opportunity for those who want to enjoy R&D and be challenged and grow in the field of AI-First software / product development. Along the way these 2 roles will contribute to game-changing products for the multi-trillion-dollar insurance industry.
Both senior candidates (i.e., with years of experience / leadership) and junior candidates are welcome to apply; we have and will offer positions appropriate to expertise and level of experience.
For AI Researcher Responsibilities:
● Analyzing problem to solve by working closely with Production team. Output is the Solution Proposal
● Analyzing data received to deeply understand the problem and visualize solutions to build up core engines of Cinnamon. Output is the Algorithm Specs Document - Pre-proceed and generate data if needed
● Pre-proceed and generate data if needed
● Quickly build, evaluate, adjust and deploy highly effective AI algorithm, basing on focused problem and solution concept
● Working closely with Production engineers to deploy AI modules in production projects
● Skills with Python, Java, C++, or other programming language, as well as with R, MATLAB or similar scripting language
● Have experiences with some deep learning packages (Tensorflow, Keras, PyTorch, Caffe, Theano)
● Ability and experiences to solve real-world problems with business value through machine learning, and statistical algorithms
● Strong desire to push your ideas into production, overcoming obstacles
● Background in machine learning with domain knowledge and experience in the following areas: data-driven statistical modeling, graphical models, feature extraction and analysis, supervised learning, discriminative methods
● An understanding of machine learning, algorithms and computational complexity
● Programming skills sufficient to extract, transform, and clean large (multi-TB) data sets in a Unix/Linux environment