San Mateo HQ
Full-time
Research
Models are what they eat. But a large portion of training compute is wasted training on data that are already learned, irrelevant, or even harmful, leading to worse models that cost more to train and deploy.
At DatologyAI, we’ve built a state of the art data curation suite to automatically curate and optimize petabytes of data to create the best possible training data for your models. Training on curated data can dramatically reduce training time and cost (7-40x faster training depending on the use case), dramatically increase model performance as if you had trained on >10x more raw data without increasing the cost of training, and allow smaller models with fewer than half the parameters to outperform larger models despite using far less compute at inference time, substantially reducing the cost of deployment. For more details, check out our recent research on synthetic data scaling (BeyondWeb) and pretraining with domain-specific data (The Finetuner’s Fallacy).
We raised a total of $57.5M in two rounds, a Seed and Series A. Our investors include Felicis Ventures, Radical Ventures, Amplify Partners, Microsoft, Amazon, and AI visionaries like Geoff Hinton, Yann LeCun, Jeff Dean, and many others who deeply understand the importance and difficulty of identifying and optimizing the best possible training data for models. Our team has pioneered this frontier research area and has the deep expertise on both data research and data engineering necessary to solve this incredibly challenging problem and make data curation easy for anyone who wants to train their own model on their own data.
Come shape the field of data research, arguably the most consequential lever of intelligence innovation. After all, it all starts with the data.
The Datology Labs Fellows Program is an environment to immerse yourself in the problems that demand our attention, with DatologyAI providing funding, compute, and mentorship. This spans work in foundation models, pre-training, mid-training, post-training, and evaluation.
The progress of all intelligence, and human innovation as a whole, will start with supporting technical talent with utmost flexibility; while focusing on the data, the genesis of our innovative progress.
Direct access to Datology's curation infrastructure, GPUs, and funding. Get instant access to more compute that most academic labs have access to. We know you have ambitious ideas. We meet you with access to pipelines, engineering infrastructure on a trillion token scale, and a passionate support system, to enable you to start innovating on data the same day you start.
Mentorship from some of the brightest and most passionate data researchers, alongside an exceptional community of data lovers excited about the same things as you!
We hope that by the end of the program you will accomplish real output in the field, via a paper, a blog post, or benchmark, or a public artifact that the community can use and build on top of.
We are looking for strong technical researchers, PhD students, postdocs or equivalent with a clear idea of what you want to explore, with strong curiosity and an ability to execute ambitious ideas with autonomy.
You are a good fit if you are:
Obsessive about data
Are mid-phd and want to dedicate 6 months to solving a frontier data research problem
being mid-phd is not a hard requirement, and we recognize that this maturity can come at all levels
Are willing to take risks and fail fast to discover the most promising research
Have strong curiosity and creativity
If you are interested and passionate about data research, we encourage you to apply, even if you don’t meet every single qualification!