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.

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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