Anicalls

ML Engineer/ Data Engineer

Job description

  • Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress
  • Managing available resources such as hardware, data, and personnel so that deadlines are met
  • Analyzing the ML algorithms that could be used to solve a given problem and ranking them by their success probability
  • Supervising the data acquisition process if more data is needed
  • 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
  • Verifying data quality, and/or ensuring it via data cleaning
  • Deploying models to production
  • Finding available datasets online that could be used for training
  • Defining validation strategies
  • Defining the preprocessing or feature engineering to be done on a given dataset
  • Defining data augmentation pipelines
  • Training models and tuning their hyperparameters
  • Analyzing the errors of the model and designing strategies to overcome them

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