The posting
Overview We are seeking a Data Research Engineer to join our AI team, where we are building the next generation of foundation models across different modalities: text, image, video, audio. If you are passionate about exploring, designing, and building high-quality datasets to drive frontier AI models, this role is for you.
At Microsoft AI, data is at the heart of innovation—and in this role, you will collaborate closely with other colleagues to curate, analyse, and evaluate diverse data sources critical to 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.
Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
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 data ingestion, pre-processing, filtering, and annotation Analyse real-world multimodal datasets to assess quality, diversity, relevance, and identify areas for improvement Build 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 Required Qualifications:
Bachelor's Degree in AI, Computer Science, Data Science, Statistics, Physics, Engineering, or a related technical field. Proficiency in Python. Experience with distributed data-processing frameworks such as Spark, Ray and workflow-orchestration tools such as Airflow. Experience with processing datasets at many petabyte scale and with trillion rows. Experience building datasets for training foundation models, including language or multimodal models. Strong experience in data analysis, data engineering, or both. Ability to communicate technical findings clearly and effectively to research, engineering, and product teams. Experience evaluating dataset quality and measuring the impact of data through controlled model-training experiments.
Preferred Qualifications:
Master’s degree in Computer Science or a related technical field, or equivalent experience. Experience working with large-scale, real-world datasets that are unstructured or semi-structured Experience evaluating dataset quality and measuring the impact of data through controlled model-training experiments. Experience with multimodal data, such as image, video, or audio data.
