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Senior Data Scientist

  • On-site
    • Yerevan, Erevan, Armenia
  • IT

Job description

  • Advanced LLM Development:
    • Implement and enhance Large Language Models using techniques like Retrieval-Augmented Generation (RAG) for improved context understanding and response generation
    • Continuously refine and fine-tune AI models to cater to specific use cases and improve overall performance
  • AI Ops and Toolchain Optimization:
    • Manage AI operations to ensure efficient deployment and maintenance of AI models.
    • Optimize AI toolchains for streamlined development, testing, and deployment of AI solutions.
  • Comprehensive Model Evaluation:
    • Develop and implement robust model evaluation frameworks to assess model performance, accuracy, and reliability.
    • Conduct thorough testing and validation of AI models to ensure they meet high-quality standards.
  • Data Analysis and Algorithm Development:
    • Analyze vast datasets to extract meaningful insights and inform model improvements.
    • Create and implement advanced machine learning algorithms tailored to specific AI applications.
  • Cross-Functional Collaboration:
    • Collaborate with various teams to integrate AI technologies into diverse products and services.
    • Lead innovation initiatives and contribute to the company's AI strategy and vision.
  • Documentation and Knowledge Sharing:
    • Maintain comprehensive documentation of methodologies, experiments, and findings.
    • Share knowledge and insights with team members and stakeholders, ensuring transparency and collaborative growth.


Job requirements

  • PhD or Master's degree in Computer Science, Data Science, Artificial Intelligence, or related fields.
  • 6+ years of industry experience.
  • Extensive experience with Large Language Models, including RAG and fine-tuning techniques.
  • In-depth knowledge of AI Ops, AI toolchains, and model evaluation methods.
  • Proficient in machine learning, deep learning, and statistical modeling.
  • Strong programming skills in Python, R, or similar languages.
  • Familiarity with AI frameworks (e.g., TensorFlow, PyTorch) and cloud-based AI services.


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