Description

  • Advanced degree in computer science, math, statistics, or a related discipline is preferable but knowledge of the domain is more important than a piece of paper.
  • Should have good knowledge of math and statistics.
  • 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.
  • 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.
  • Finding available datasets online that could be used for training. 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.

Skills

  • Proficiency with a deep learning framework such as TensorFlow or Keras or PyTorch.
  • Proficiency with Python and basic libraries for machine learning such as sci-kit-learn, pandas, and NumPy.
  • 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.

Benefits

  • Competitive Salary
  • Start-up environment which allows for creativity and fun
  • A pleasant working environment with enthusiastic and friendly teams
  • Possibility of personal growth and to take over responsibilities
  • Flexible work hours
  • Employee referral bonus program