Google Cloud AI Engineer Intern

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WorkplaceHo Chi Minh


  • Startup company with promotion opportunities.
  • Professional working environment with many attractive training and compensation policies.
  • Cloud Ace is the official Google Cloud Partner in Vietnam (Google Cloud Premier Partner) so you will have many opportunities to learn Google Cloud certifications such as Professional Cloud Architect, Professional Data Engineer, Professional Machine Learning Engineer.
  • Access the public cloud platform with the world’s most advanced technologies from Google.
  • Help you create a new break-through in knowledge in your field.
  • With the support of experienced members of the team, help you get Google Cloud certificates “Cloud Architect”, “Data Engineer”, “Cloud Engineer”.
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  • Investigate and develop AI-based applications.
  • Up-to-date technical knowledge in Cloud service, Big Data and Machine Learning related field.
  • Convert the machine learning models into application interfaces (APIs) in order that other applications can use it.
  • Deployment of AI and ML models at scale in the cloud, and on integrating them with existing products and IT systems.
  • Collaborating with our Data & Business Intelligence teams.
  • Be an honest team player, as coordinating with others may be a must.


  • Love of data. You run “SELECT COUNT(SHEEP) FROM BACKYARD” during your sleep!
  • Computer Science Fundamentals and Efficiency Programming (include data structures, algorithms, computability and complexity, computer architecture, etc.)
  • Understanding ML lifecycle concepts.
  • Basic knowledge of the different types of machine-learning algorithms; familiarity with frameworks like Tensorflow and PyTorch.
  • Programming languages, such as Python, R, Java, and C++ to build and implement models (Python is referred).
  • Know a little about writing SQL queries.
  • Non-Technical Skills: Communication & Problem-Solving.

  • Experience with Google Cloud Platform products (Bigquery & AI/ML services).
  • Hands-on experience with data processing.
  • Model deployment experience on cloud platforms like Google Cloud.
  • Analysis and feature selection using analytic tools and ETL/ELT frameworks (Apache Spark, Hive, Amazon, Athena, etc.).
  • Set up and manage AI development and product infrastructure.

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