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Five9
AI

Data Scientist/AI Trainer

Five9 · Remote, US · $90k - $250k

Actively hiring Posted 4 months ago

Responsibilities

  • Develop and maintain Python code for data analysis, model evaluation, and the automation of AI workflows.
  • Design, implement, and evaluate sophisticated prompts for Large Language Models (LLMs) to optimize performance across various conversational tasks.
  • Integrate and fine-tune Speech-to-Text (STT) and Text-to-Speech (TTS) models to ensure high-quality, natural-sounding voice interactions.
  • Implement and improve robust methods to quantitatively and qualitatively compare and evaluate LLM outputs.
  • Collaborate with Data Scientists and Engineers to identify technical requirements, prioritize tasks, and architect scalable AI solutions.
  • Create and curate multilingual speech and text datasets to train and benchmark models.
  • Evaluate, recommend, and implement machine learning models for tasks such as topic modeling, summarization, and intent classification.
  • Develop data visualization tools and dashboards to monitor model performance and provide insights to stakeholders.

Basic qualifications

  • Master's degree in Human-Computer Interaction, Computer Science, Cognitive Science, Linguistics, or a similar technical field.
  • Proven experience in Python programming for data science, machine learning, or software development.
  • Solid understanding of Conversational AI concepts and the underlying technologies.
  • Strong attention to detail and a commitment to maintaining high-quality standards in code and model performance.
  • Demonstrated ability to work independently and as part of a collaborative, customer-facing team.
  • Excellent technical communication skills.
  • Fluent in English, both written and spoken.

Preferred qualifications

  • Graduate degree or higher in Computer Science, Computational Linguistics, or a related field.
  • Fluency in Spanish and/or Portuguese.
  • Deep hands-on experience with LLMs, including prompt engineering, fine-tuning, and evaluation techniques.
  • Expertise in Speech-to-Text (STT) and Text-to-Speech (TTS) technologies and their practical application in conversational AI systems.
  • Proficiency with ML libraries and platforms such as Scikit-learn, TensorFlow, PyTorch, R, Jupyter, and SQL.
  • Experience in a customer-facing role, including technical requirement gathering and presentations.
  • Experience with bot frameworks such as IBM Watson, Amazon Lex, Rasa, or Google Dialogflow.

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