Research Scientist Intern
Databricks
Research Scientist Intern
Databricks
Builds cloud software for data analysis and AI
Company Description:
Are you interested in tackling one of the hardest, most important open problems in deep learning: making training more efficient and cost-effective? MosaicML is a startup doing just that. Motivated by dramatic increases in model sizes and computing costs, we focus on developing fundamental innovations to improve the efficiency of training. We conduct the scientific research necessary to ensure that the capabilities unlocked by modern deep learning are accessible to everyone and sustainably scalable.
MosaicML is unique in our approach to this problem: we’re focused on every level of the stack, including the choice of hardware, the machine learning systems, the training algorithm, and the multi-run workflow by which scientists arrive at final models. We’re developing methods that alter the training algorithm (optimization procedure, model, and data) and training infrastructure to reduce resource usage and make the most of every cycle, watt, and dollar. This requires rigorous empirical research. Our researchers study how neural networks learn, develop methods to leverage these findings, and understand whether they work as intended. In short, research at MosaicML involves advancing the scientific frontier in service of making deep learning practical and efficient for everyone.
Job description:
You will work with one or more researchers on a project that will advance our existing projects toward making neural network training more efficient. This may include:
Your qualifications and qualities:
Additional Notes:
Builds cloud software for data analysis and AI
Databricks builds cloud software that businesses use to organize data, analyze it, and develop AI applications. Its lakehouse architecture brings the flexible storage of a data lake together with the querying and management tools of a data warehouse. Data engineers prepare and update datasets, analysts build reports, and developers train models or create applications in a shared workspace with controls over who can use the data. The platform runs on Amazon, Microsoft, and Google clouds, and customers pay for computing usage or commit to longer contracts for discounted rates. Databricks was founded in 2013 and is headquartered in San Francisco, California.
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