
DatologyAI provides automated data curation to improve AI model training and performance. The platform uses deep learning to automatically select relevant data, augment datasets, and optimize…

DatologyAI provides automated data curation to improve AI model training and performance. The platform uses deep learning to automatically select relevant data, augment datasets, and optimize…
What they do: Automated, modality-agnostic data curation platform to improve AI training efficiency and reduce compute costs
Founded: 2023
HQ: Redwood City, California, United States
Latest disclosed round: Series A, May 8, 2024
Total capital raised: $57.65M (reported)
Data quality and dataset selection for AI model training at scale.
2023
Technology, Information and Internet
$11,650,000
Seed reported with participation from Radical Ventures, Conviction, Outset Capital, Quiet Capital and angels
$46,000,000
Series A reported to bring total capital raised to more than $57.5M
“Combination of institutional VCs (Amplify Partners, Felicis, Radical Ventures, Conviction Capital, Outset Capital, Quiet Capital, M12, Amazon Alexa Fund) and prominent angel/technical investors (Jeff Dean, Geoffrey Hinton, Yann LeCun, Adam D'Angelo, Aidan Gomez, Ivan Zhang, Douwe Kiela, Naveen Rao, Jascha Sohl-Dickstein, Elad Gil)”
| Company |
|---|
About The Company 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 blog posts sharing our high-level results for text models and image-text models.
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.
This role is based in Redwood City, CA. We are in office 4 days a week.
About The Role We are looking for a Technical Sourcer who is excited to help build an exceptional team of engineers and researchers from the ground up. In this role, you will partner closely with the team and leadership to shape how we find, engage, and attract top technical talent. You will own and evolve our sourcing engine, develop creative approaches to reaching hard-to-find candidates, and drive the top of the funnel for some of the most important roles at the company. This is a chance to have real impact early, influence our hiring strategy, and help define what great looks like as we scale!
What You'll Work On
About You
Compensation At DatologyAI, we are dedicated to rewarding talent with highly competitive salary and significant equity. The base salary for this position ranges from $120,000 to $145,000.
We offer a comprehensive benefits package to support our employees' well-being and professional growth:
Your next opportunity is in here somewhere. Sign up to explore 70,000+ startups and their open roles. No spam. No gamification. Just jobs.
70,000+
Startups
83,000+
Open Roles
4,800+
New This Week
Drive top-of-funnel strategy by identifying and engaging world-class researchers and engineers
Relentlessly experiment with sourcing and outreach methods, using data to refine messaging and maximize response rates
Develop creative sourcing strategies that go far beyond LinkedIn:
Surface talent from research papers, academic publications, and conference proceedings
Track open-source contributions, GitHub repos, and technical blogs
Engage with niche communities, forums, and specialized networks
Craft compelling, highly personalized outreach and continuously A/B test messaging to improve engagement
Partner closely with leadership and engineering teams to translate complex technical requirements into effective search parameters
Build and maintain robust pipelines of specialized talent for our most critical roles
Own candidate experience from first touch through initial screening, including scheduling conversations
Analyze funnel metrics to spot opportunities, double down on what works, and cut what doesn’t