We are seeking engineers and researchers to join our Pretraining Text Data team, where we are building the next generation of foundation large language models. If you are passionate about designing and curating high-quality datasets to power frontier AI models, this role is for you.
In this role, you’ll work at the intersection of data and innovation—collaborating with scientists, engineers, and annotators to curate, analyze, and evaluate diverse text datasets critical to model development. You will lead efforts to:
- Develop novel data collection strategies
- Improve dataset quality and integrity
- Understand data-driven model behaviours
- Train models to understand the impact of data and data mixes
- Align datasets with ethical and societal values
This is a cross-disciplinary, high-impact role ideal for engineers and researchers who want to push the boundaries of what AI can learn from data.
Microsoft Superintelligence Team
The Microsoft Superintelligence Team is a startup-like team inside Microsoft AI, created to push the boundaries of AI toward Humanist Superintelligence—ultra-capable systems that remain controllable, safety-aligned, and anchored to human values. Our mission is to create AI that amplifies human potential while ensuring humanity remains firmly in control.
Responsibilities
- Create high-quality datasets for training and evaluation; run experiments on new datasets (data ablations) to assess their impact and determine the most effective data.
- Develop and maintain scalable data pipelines for text data ingestion, preprocessing, filtering, and annotation.
- Analyze real-world text datasets to assess quality, diversity, relevance, and identify areas for improvement.
- Build lightweight tools and workflows for dataset auditing, visualization, and versioning.
- Collaborate with Safety, Ethics, and Governance teams to ensure datasets meet standards for quality, privacy, and responsible AI practices.
Qualifications
- Bachelor’s Degree in AI, Computer Science, Data Science, Statistics, Physics, Engineering, or related technical discipline AND technical engineering experience with coding in languages including, but not limited to, Python and common data libraries (Pandas, NumPy, etc.) OR equivalent experience.
- 2+ years of experience in data analysis or data engineering, including work with large-scale datasets that are unstructured or semi-structured.
- Proficiency in statistics and exploratory data analysis methods.
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