Type Full-Time, Part-Time
Location Remote
Level Lead, Senior

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Job Description

Research and implement the latest machine learning and statistics related models, modify, tune and verify them, and apply them to products to solve user problems.


  1. ML architecture design and decision
  2. ML model development / improvement / maintenance
  3. Data analysis
  4. Participate in the discussion of AI algorithms and the possibility of trying more solutions
  5. Measure the accuracy of the AI Model and make adjustments so that the model can solve customer problems more accurately
  6. Study the latest papers and try to apply them in business scenarios
  7. Participate in and experience the agile development process
  8. We are still growing and innovating, and there will be new and more challenging new jobs at any time

Team Work

Work with team members to develop and implement AI projects. Research, test, review, provide feedback, create AI/ML/RPA-related projects.

  1. Master data analysis/cleansing and other data science technologies to understand data and design model architecture.
  2. Identify and select AI/ML technologies to solve problems.
  3. Deploy and integrate AI ​models into back-end servers and build up front-end interfaces.


  1. Degree in computer science or statistics
  2. Passionate about researching AI, familiar with new AI/ML technologies

Familiar with

  1. Machine Learning/Artificial Intelligence
  2. Data mining
  3. Deep learning, artificial neural network
  4. Tree search techniques
  5. Reinforcement learning
  6. Game theory
  7. Robotic process automation (RPA) workflow automation

You Should Have…

  1. Experience in creating ML systems in the enterprise, and using it in commercial products
  2. Familiar with any ML OpenSource tool, such as tensorflow
  3. Git
  4. Testing
  5. CI/CD

Additional desired competencies

  • Familiar with at least one programming language (e.g., C#, Python, C++)

We hope you are the one …

  1. People who are actively responsible, actively contributing, and continuous learning
  2. Have a high degree of enthusiasm for ML work
  3. Have a proactive, responsible, and active work attitude
  4. Have good communication and teamwork skills
  5. Be willing to learn and share, and continue to receive new knowledge
  6. Have the experimental spirit to try bravely

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