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Machine Learning and Artificial Intelligence Engineer at Qimia Inc. (San Diego, CA)

Qimia Inc is an international Machine Intelligence Startup with 80+ Engineers and Data Scientists. We develop the next-generation technologies that change how people use, interact with, explore and gain insight from data.We are seeking highly motivated individuals to join us as Machine Learning and Artificial Intelligence Engineers. Through our intensive and comprehensive training, you will become familiar with top performant and cutting-edge technologies and tools that are part of our stack. You will become familiar with our products and services to develop and integrate best-in-class solutions.Awaiting you is a stimulating and challenging work atmosphere with flat hierarchies and friendly experienced colleagues. Here at Qimia we put a strong focus on the comprehensive training and education of our Engineers and Data Scientists.Topics covered in training:Big Data Science:Python Machine Learning Libs (NumPy, SciPy, Pandas, Jupyter, Scikit-learn, Theano, TensorFlow, NLTK), Spark for Data Mining and Machine Learning (Spark SQL, Spark ML, PySpark)Deep Neural Networks:Feed-Forward neural nets, Convolutional neural nets, Recurrent neural nets, development of production-ready TensorFlow and PyTorch and Keras.Data Science and Machine Learning Essentials:Time Series and Sequential Data processing, Supervised and Unsupervised Machine Learning, Classification, Logistic Regression and Random Forest, Support Vector Machines, K-Nearest Neighbors, Naive Bayes and Gradient BoostingWeb and Text Mining:Natural Language Processing and Information Retrieval, Categorizing and automatic Tag/Keyword extraction, Document Classification and Clustering, Entity Recognition, tf-idf, N-grams, word2vec and gensim etc.In our training, we work intensively on current and previous Kaggle competitions in areas of Deep Learning, Predictive Analysis, Recommendation Engines and Natural Language Understanding Job DetailsBuild cutting-edge Artificial Intelligence and Machine Learning applicationsDevelop Recommendation Engines, Web and Text Data Mining using Natural Language Understanding models, applying Network and Graph Analysis algorithms and tools, training Deep Neural NetworksPerform end-to-end design and implementation of data analytics systems; this includes data gathering, requirement engineering, and specification, as well as the conceptualization of technical solutions based on business needsWork closely with teams of Data Scientists and Engineers to identify opportunities for design and implementation of internet scale Data Mining solutionsDevelop ETL pipelines for large, complex datasets; Processing of structured and unstructured data, using Cloud Native Spark and SQL ServicesPrototype and implement massive scalable Data Analytics solutions, using cloud big data toolsWork with Cloud Platforms (AWS, MS Azure, IBMC, and Google Computing Engine)Basic QualificationsMS degree or equivalent in Computer Science or relevant quantitative disciplines like statistics, operations research, bio informatics, mathematics or physics1 year of work or educational experience in Machine Learning and Artificial Intelligence1 year of relevant experience in data analysis fields (statistics/data science)Experience with one or more general purpose programming languages such as Java, C/C++, Python, Scala or RPreferred QualificationsMS in Computer Science, Artificial Intelligence, Machine Learning or related technical fieldsExperience with one or more of the following: Natural Language Processing and Understanding, Classification, Pattern Recognition and Recommendation SystemsExperience in dealing with large amounts of data, e.g., social network data, scientific data, sensor data, etc.Applied machine learning experience on large datasetsProven programmer experience in at least one programming language, such as Java, Scala, C++, or a similar object-oriented languageExperience or Knowledge in the following is an advantage:Hadoop, HDFS, HiveSpark, Databricks, EMR, AWS GlueCloud Platforms (AWS, MS Azure, and Google Computing Engine)Spark ML, H2O, Python ML and Data Science Libs (NumPy, SciPy, Pandas, IPython, Scikit-learn, Keras, TensorFlow)