CarbyneTech - Data Science Engineer - Machine/Deep Learning Models

Job Description

- Experience in research and development. Conference papers at reputed AI/ML platforms (ICML, NIPS, AAAI) will be a big plus, - Experience in Time series modeling (classical methods like ARIMA, STL Forecast). Understanding and implementing active research in Time series forecasting (Bayesian Forecasting, Hierarchical Forecasting), - Hands-on experience in implementing Deep learning models with textual data/ time series data (CNN, LSTM- s) will be a great plus, - Expertise in SCALA (or) functional programming paradigm/ Python / R, - Experience in big data technologies like Spark, Hive, Hadoop, - Experience in understanding business needs and translating to a data-science problem, - Knowledge of the Industry 4.0 process - inventory optimization, smart factory, times optimization, quality control, and industrial automation,Python - Libraries : tensorflow, Keras, Numpy, sklearn, google-cloud-vision, pandas, imutils, ezdxf, imgaug, lxml, opencv-contrib-python-headless, scikit-image, matplotlib - Review deployments, source codes, configurations, algorithms, models, repositories for completeness - Identify missing libraries/codes, dependencies, code documentation - Update technical documentation, code comments, etc - Integrate the code into DevOps - Testing - DevOps Pipeline Deployment, Prepare simulation script for stress test, Test for horizontal vertical scalability, Test for integration with Google OCR, AWS Textract, Active Directory, User Management, Test for performance, User Journeys"