Description
We are seeking a Member of Technical Staff to join the AI Data Platform team at Microsoft AI. The successful candidate will contribute to building the world's most advanced multimodal dataset, which will power the training of frontier AI models.
The AI Data Infra team is responsible for designing and implementing data infrastructure to support the creation of large-scale training datasets. The ideal candidate will have expertise in data engineering, distributed systems, and AI technologies.
Responsibilities:
- Develop and evolve large-scale AI data infrastructure for frontier AI labs, focusing on data collection, ingestion, cleaning, curation, and governance.
- Lead the development of intelligent multimodal data processing systems for text, images, video, and documents.
- Design and implement AI-native data pipelines that leverage LLMs, VLMs, and agents to automate data operations.
- Develop AI-optimised storage solutions using Lance, Iceberg, Paimon, and Parquet.
- Discover and build rare, high-value datasets for challenging domains.
- Drive the data-model-evaluation iteration loop to identify data gaps and improve model performance.
- Collaborate with model researchers and training engineers to construct training data and evaluate model performance.
Qualifications:
- Master's degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field with 3+ years of experience in business analytics, data science, software development, data modeling, or data engineering.
- Experience with distributed data platforms such as Spark, Flink, or Ray.
- Proficient experience in Python and experience with SQL and Shell.
- Experience with multimodal data (text, image, video, or audio).
Preferred Qualifications:
- Hands-on experience building datasets for LLM/VLM/multimodal model pre-training or post-training.
- Experience with synthetic data generation, including text generation, image-text synthesis, and multimodal trajectory generation.
- Familiarity with major evaluation benchmarks such as MMLU, MMBench, and MM-BrowseComp.
- Experience with open file and table formats such as Lance, Iceberg, Paimon, and Parquet.
Salary Range: The typical base pay range for this role across the U.S. is USD $142,800 – $274,800 per year. For specific work locations within the San Francisco Bay area and New York City metropolitan area, the base pay range is USD $188,000 – $304,200 per year and USD $220,800 – $331,200 per year respectively.