Researcher

Clarisse Simoes Ribeiro

Also known as Clarisse Simões Ribeiro

Clarisse Simoes Ribeiro is an AI engineer whose work spans dialogue systems, small language models, and hallucination reduction. She earned an electrical-engineering degree and worked as a Lead Software Engineer in Brazil before pursuing machine-learning study through a Microsoft scholarship. She built an Azure AutoML project, hosted a Microsoft Reactor skills panel in March 2022, and contributed to Microsoft Research’s GODEL dialogue model in June 2022. In November 2023, she was a Software Engineer II at Microsoft Research and coauthored Orca 2; in 2024, she coauthored an ICLR paper on teaching language models to hallucinate less with synthetic tasks.

Timeline

  1. By 2020

    An electrical-engineering degree

    By 2020, she holds an electrical-engineering degree and remains interested in computer science and coding.

  2. 2020

    Software leadership in Brazil

    In 2020, she works as a Lead Software Engineer at a multinational company in Brazil’s electronics and semiconductor industry.

  3. 2020

    A machine-learning scholarship

    In 2020, she gets the opportunity to pursue Microsoft’s scholarship for Udacity’s Machine Learning Nanodegree as her interest in machine learning and data science grows.

  4. December 2020

    An Azure AutoML project

    In December 2020, she builds a project that applies AutoML to bank-marketing data and deploys its best model as an authenticated Azure Container Instance with an HTTP API.

  5. March 2022

    A Microsoft Reactor panel

    In March 2022, she hosts Microsoft Reactor’s Portuguese panel on soft and hard skills, where the speakers discuss ways to plan professional learning.

  6. June 2022

    Contributing to GODEL

    In June 2022, she contributes to Microsoft Research’s GODEL work, a grounded dialogue model that supports task-oriented and social conversation.

  7. November 2023–2024

    Orca 2 and ICLR research

    In November 2023, she is a Software Engineer II at Microsoft Research and coauthors Orca 2, which fine-tunes 7B and 13B models with tailored synthetic data to improve reasoning. In 2024, she coauthors the ICLR paper Teaching Language Models to Hallucinate Less with Synthetic Tasks.

Sources and credits

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  1. How the Machine Learning Scholarship Program for Microsoft Azure Changed Students’ Lives (Part 1) | Udacity udacity.com. Checked 19 October 2026.
  2. Machine Learning Engineer with Microsoft Azure: Project 2 – Operationalizing Machine Learning github.com. Checked 19 October 2026.
  3. Soft e Hard Skills para carreira em Tecnologia, por Mulheres na tecnologia @MS | Microsoft Reactor developer.microsoft.com. Checked 19 October 2026.
  4. GODEL: Combining goal-oriented dialog with real-world conversations - Microsoft Research microsoft.com. Checked 19 October 2026.
  5. Orca 2: Teaching Small Language Models How to Reason - Microsoft Research microsoft.com. Checked 19 October 2026.
  6. Orca - Microsoft Research: Publications microsoft.com. Checked 19 October 2026.
  7. Microsoft at ICLR 2024 - Microsoft Research microsoft.com. Checked 19 October 2026.