Stefan Baumann

Machine Learning Engineer at Moveworks

San Francisco, California, United States

About

Interested in AI agents, neurotechnologies (BCIs), deep learning/RL, and psychedelic research

Experience

  • Moveworks (4 yrs 1 mo)
    • Staff Machine Learning Engineer
      Apr 2026 - Present · 4 mos

      ServiceNow acquired Moveworks for $2.85B Building the next AI Agent harness for the workplace based on reasoning models.

    • Senior Machine Learning Engineer
      Sep 2023 - Apr 2026 · 2 yrs 8 mos

      Built and scaled the Moveworks AI Assistant for employee support. Lead Quality and Evals for our AI Agent system. Focused on AI agent frameworks, building tools/plugins, creating end-to-end evaluation pipelines, implementing customer-facing customization & alignment/steerability tools, and conducting prompt engineering experiments with human & LLM-based annotation (LLM-as-a-judge).

    • Machine Learning Engineer
      Jul 2022 - Sep 2023 · 1 yr 3 mos

      Core contributor to MoveLM, our in-house fine-tuned Large Language Model, specifically for function calling, instruction following, and aligned (safe) outputs. Implemented various synthetic data generation techniques (including Self-Instruct) and lead SFT + iterative DPO training & evaluations/benchmarking.

  • AI Engineer at Avey
    Feb 2022 - May 2022 · 4 mos

    - Worked on the integration of Natural Language Processing (NLP) models to support Avey’s medical AI assistant designed for self-diagnosis - Researched health insurance claim processing

  • Developer & Data Specialist at NeuraLace Medical
    May 2021 - Aug 2021 · 4 mos

    - Structured and developed a full-stack web app for scaleable data collection of therapists treating NeuraLace's patients - Implemented multiple new features to NeuraLace’s website to prevent spam and optimize NeuraLace’s lead collection process - Created a data reporting and visualization system to improve the team’s data analysis efficacy and efficiency on leads inside Salesforce - Designed experiment and wrote the study proposal for a randomized, controlled dose-optimization study, intended to find an optimal treatment schedule for NeuraLace's AxonTherapy

  • Data Scientist at HE-Arc - Haute École Arc
    Jul 2020 - Aug 2020 · 2 mos

    ⁃ Made a sensor network map to simplify complex and large real-world data sets - Preprocessed data using methods for outlier detection/correction, resampling, and missing values imputation (using scikit-learn Python library) - Integrated general methods for evaluating data sets and models, which included defining new dimensionless evaluation metrics - Developed a working pipeline for modeling a predicted feature (using Keras Python library) Worked together with the data analytics research group and engineers from AFRY Schweiz AG, which was the corporate partner for this research.