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AIML Engineer at NirYu. Location Information: Remote, Mexico. . Job Responsibilities:. . Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress.. . Analyzing the ML algorithms that could be used to solve a given problem and ranking them by their success probability. Determine and refine machine learning objectives.. . Designing machine learning systems and self-running artificial intelligence (AI) software to automate predictive models.. . Transforming data science prototypes and applying appropriate ML algorithms and tools.. . Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world. . Ensuring that algorithms generate accurate user recommendations.. . Verifying data quality, and/or ensuring it via data cleaning.. . Supervising the data acquisition process if more data is needed.. . Defining validation strategies.. . Defining the pre-processing or feature engineering to be done on a given dataset. . Solving complex problems with multi-layered data sets, as well as optimizing existing machine learning libraries and frameworks.. . Developing ML algorithms to analyze huge volumes of historical data to make predictions.. . Running tests, performing statistical analysis, and interpreting test results.. . Deploying models to production.. . Documenting machine learning processes.. . Keeping abreast of developments in machine learning.. . Job Requirements:. . Bachelor's degree in computer science, data science, mathematics, or a related field.. . Knowledge as a machine learning engineer. Proficiency with a deep learning framework such as TensorFlow, XgBoost, Wavevnet, Keras, numpy.. . Advanced proficiency with Python, Java, and R code writing.. . Proficiency with Python and basic libraries for machine learning such as scikit-learn and pandas.. . Extensive knowledge of ML frameworks, libraries, data structures, data modeling, and software architecture in ANN, CNN, RNN with LSTM.. . Ability to select hardware to run an ML model with the required latency. . In-depth knowledge of mathematics, statistics, and algorithms.. . Superb analytical and problem-solving abilities.. . Great communication and collaboration skills.. . Excellent time management and organizational abilities.. . .