The Cloud AI team is hiring motivated and productive Data Scientist 2 passionate about working on building our next generation machine learning and artificial intelligence platforms for the cloud. The ideal candidate for this particular role will have both a good understanding of how data scientists work today, as well as relevant work experience as a Data Scientists. You will be part of a passionate team building a these cloud services for training and inferencing machine learning workloads that can scale on large dataset, staying up-to-date with the latest state-of-the-art deep learning techniques and algorithms. We use open source technologies and Github for our work and often collaborate with the community at large. A potential candidate must ideally have a Masters (Ph.D. is a plus) in computer science or related data science fields, and have strong data science fundamentals (statistics, machine learning, deep learning), and be comfortable to wear many hats to get the job done including
The Applied Data Scientist will deal with a wide range of data science problems to devise and deploy best of breed solutions. These are first and third party problems ranging from classification algorithms to using DNNs and everything in between. You will work on a key initiative that'll be shipped in the Azure ML platform. The purpose is to arm end users without deep data science knowledge to solve AI problems in the most efficient and expedient manner in their respective domain. This will cut short the normal cycles of development for Machine learning and Deep learning models, ultimately moving
Masters or PhD in Data Science, Machine Learning, AI, Computer Science or Statistics is highly desired. 5+ years of proven track record of applied data science for practical problems using ML/DL techniques including but not limiting to DNNs is highly desired. Deep expertise in one or more of the frameworks Scikit learn, TLC, Keras, TensorFlow, CNTK, H2O, Caffe, PyTorch, R Expertise in Python, C#, Open source tools and languages, experience working big data tools like Spark, HDI, Hadoop etc. Customer empathy, resourcefulness, initiative and proactiveness are a must. Passionate about building a product