Microsoft AI is seeking Data Research Engineers to join the Multimodal team, building the next generation of foundation models across vision, language, audio, and beyond. You will curate, analyze, and evaluate diverse multimodal data sources to drive model development. You’ll lead efforts in developing novel data collection strategies, improving dataset quality, understanding data-driven model behaviours, and aligning datasets with ethical and societal values. This is a cross-disciplinary, high-impact role ideal for engineers who want to push the boundaries of what AI can learn from data, especially in multimodal contexts. Responsibilities include: 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 multimodal ingestion, pre-processing, filtering, and annotation; Analyse real-world multimodal 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 a related technical field AND technical engineering experience with coding in languages including, but not limited to, Python and common data libraries (Pandas, NumPy, etc.) OR equivalent experience; Exp

Microsoft AI is seeking Data Research Engineers to join the Multimodal team, building the next generation of foundation models across vision, language, audio, and beyond. You will curate, analyze, and evaluate diverse multimodal data sources to drive model development. You’ll lead efforts in developing novel data collection strategies, improving dataset quality, understanding data-driven model behaviours, and aligning datasets with ethical and societal values. This is a cross-disciplinary, high-impact role ideal for engineers who want to push the boundaries of what AI can learn from data, especially in multimodal contexts. Responsibilities include: 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 multimodal ingestion, pre-processing, filtering, and annotation; Analyse real-world multimodal 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 a related technical field AND technical engineering experience with coding in languages including, but not limited to, Python and common data libraries (Pandas, NumPy, etc.) OR equivalent experience; Exp