NL/ML Engieer

Responsibilities:

• Model Development: Develop and train natural language processing (NLP) and machine learning (ML) models to address specific challenges within the "Democracy Upgrade" project. This could include:

  • Sentiment analysis of public opinion

  • Detection of misinformation and fake news

  • Automated summarization of policy documents

  • Personalized recommendations for civic engagement

  • Development of AI-powered debate moderation tools

• Data Processing: Process and analyze large datasets of text and other data sources relevant to the project.

• Model Optimization: Fine-tune and optimize models for accuracy, efficiency, and fairness.

• Deployment and Monitoring: Deploy models into production environments and monitor their performance.

• Ethical Considerations: Be mindful of the ethical implications of using NLP/ML in the context of democracy, working to mitigate biases and ensure fairness.

• Open Source Contribution:

  • Leveraging Open Source: Utilize and contribute to existing open-source NLP/ML libraries and frameworks (e.g., Hugging Face Transformers, spaCy, Gensim, TensorFlow, PyTorch).

  • Model Sharing: Explore opportunities to share developed models and datasets with the open-source community (with appropriate anonymization and ethical considerations).

  • Community Engagement: Participate in relevant open-source communities by:

    • Contributing to the development of NLP/ML tools and libraries.

    • Sharing knowledge and insights through blog posts, presentations, or online forums.

    • Engaging in discussions and collaborations with other researchers and developers.

    
    

• Qualifications:

  • Strong understanding of NLP and ML algorithms and techniques.

  • Experience with NLP/ML libraries and frameworks (e.g., spaCy, NLTK, TensorFlow, PyTorch).

  • Proficiency in Python or another language suitable for data science.

  • Experience with data preprocessing and feature engineering.

  • Familiarity with cloud-based ML platforms (e.g., AWS SageMaker, Google AI Platform).

  • Strong analytical and problem-solving skills.

  • Open Source Familiarity: Demonstrated experience using and contributing to open-source NLP/ML projects.

  • Understanding of Open Source Licenses: Familiarity with different open-source licenses and their implications for sharing and using code and data.

  • Bonus: Experience with explainable AI (XAI) techniques, knowledge of political science or social sciences.