- 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
- Supervising the data acquisition process if more data is needed
- 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
- Deploying models to production
- Proficiency with a deep learning framework such as TensorFlow or Keras
- Proficiency with Python and basic libraries for machine learning such as scikit-learn and pandas
- Expertise in visualizing and manipulating big datasets
- Proficiency with OpenCV
- Familiarity with Linux
- Ability to select hardware to run an ML model with the required latency
- Opportunity to work with reputable and well-known industry stakeholders in the domain of animation and image processing.
- Easy environment to work in.
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