Machine Learning Engineering


  • Working with large and complex datasets, comprising but not limited to, social media texts, images, and geo-locations.
  • Developing and evaluating AI models for different use cases in a continuous delivery environment.
  • Designing new dataset and preparing data for new applications.
  • Extending and maintaining AI automation in the organization.Qualification
  • Applicants from every training background are welcome (our team has people from anthropology, computer science, industrial engineering, and linguistics training).
  • Python, basic regular expression, and basic SQL is preferred.
  • Fluently able to explain how your code/model is working and why you designed it this way.
  • Experienced in at least one of the following areas: computer vision, information retrieval,and natural language processing, and pattern recognition. Internship and self-directedlearning projects can be counted.
  • Optional: Experience with some of these data analysis libraries and machine learningarchitectures, like Caffe2, MXNet, pandas, Scikit-learn, TensorFlow, and Torch, is a plus.
  • Optional: Experience with Unix-based server and cloud platform management (AWS,Google Cloud) is a plus.
  • Optional: Experience in software development with a virtual environment or container likeDocker or Python’s venv is a plus.
  • Excellent problem solving, critical thinking, and interpersonal skills


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