Help build the world’s most advanced multimodal dataset at Microsoft AI.
We are on a mission to create the largest and most advanced multimodal dataset in the world. This dataset, spanning all modalities from across the web and beyond, will power the training of the world’s most capable AI frontier models, pushing the boundaries of scale, performance, and product deployment.
The AI Data team at Microsoft AI is responsible for all aspects of data preparation to support our model pre-training operations, including collecting data from the source, extracting and transforming the most useful data, and understanding the impact of changes to data by training and evaluating new models. We are an interdisciplinary team of engineers and scientists, learning from each other, and collaborating to create the best models and products. We work closely with the teams that transform pre-trained models into the models that power the consumer Copilot experience.
We are looking for outstanding individuals excited about contributing to the next generation of systems that will transform the field. In particular, we are looking for candidates who:
- Are passionate about the role of data in large-scale AI model training
- Will thrive in a highly collaborative, fast-paced environment
- Have a high degree of craftsmanship and pay close attention to details
- Demonstrate a proactive attitude and enthusiasm for exploring new methods and technologies
- Effectively manage multiple responsibilities and can adjust to shifting priorities.
Responsibilities
- Design and develop data pipelines that ingest enormous amounts of multi-modal training data (text, audio, images, video).
- Build and maintain cutting-edge infrastructure that can store and process the petabytes of data needed to power models.
- Partner with the pretraining and post-training teams to improve our data recipe by rigorous and careful experimentation.
- Collaborate with the product team and other engineers and researchers across Microsoft AI to identify gaps in the current generation of models.
- Embody our culture and values.
Qualifications
Required/Minimum Qualifications
- Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND experience in business analytics, data science, software development, data modeling or data engineering work
- OR Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND experience in business analytics, data science, software development, or data engineering work
- OR equivalent experience.
- Experience using data processing technologies for Multimodal dataset scalability, parellel processing, data handling, streaming/batch processing, etc.
- Experience working with distributed computing tools such as; Spark, Kubernetes, TensorFlow, Flink and Pyspark.
- Experience conducted research in Machine Learning or worked as an ML Engineer/ MLOps/ SWE.
- Experience designing and developing data pipelines that ingest enormous amounts of multi-modal training data (text, audio, images, video) AND have the skills to be able to build infrastructure to support this work from ground up.
Preferred:
- Experience working with large scale of data ideal Petabyte scale or above.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.
Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.
