Data scientist

4 weeks ago

McLean, United States eTeam Full time
  • Over 5 years of experience with a strong experience working with Python and machine learning technologies.
  • Design, develop, and maintain Java-based applications using Spring Framework and microservices architecture.
  • Need to have a deep understanding of how language models like GPT work, including their architecture, training methodology, and capabilities.
  • Need to have good knowledge of Tokenization: Tokenization is the process of breaking down text into smaller units (tokens) for analysis. Should be familiar with different tokenization techniques and their implications for prompt engineering.
  • Need to have good understanding of various Text Generation Techniques, including techniques for controlling the output of language models through prompts, prefixes, and conditioning.
  • Should have expertise in designing effective prompts tailored to specific tasks and objectives, since prompt engineering involves crafting input prompts or instructions to guide the language model's output.
  • Strong Fine-tuning Strategies skills, which involves adapting pre-trained language models to specific tasks or domains by providing task-specific data and fine-tuning parameters. Should know how to effectively fine-tune models for optimal performance.
  • Should be familiar with evaluation metrics commonly used to assess the quality and performance of text generation tasks, such as perplexity, BLEU score, ROUGE score, and human evaluation.
  • Should be familiar with Bias Mitigation, since potential biases present in language models. Should understand techniques for mitigating biases in model outputs, such as debiasing strategies and fairness-aware training.
  • Should have skills in interpreting and analyzing model outputs to understand how prompts influence the generated text and identify patterns or biases in the model's behavior.
  • Troubleshoot and debug issues, providing timely resolution to ensure smooth operation of applications.
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