
DatologyAI builds tools to automatically select the best data on which to train deep learning models. Our tools leverage cutting-edge research—much of which we perform ourselves—to identify redundant, noisy, or otherwise harmful data points. The algorithms that power our tools are modality-agnostic—they’re not limited to text or images—and don’t require labels, making them ideal for realizing the next generation of large deep learning models. Our products allow customers in nearly any vertical to train better models for cheaper.

DatologyAI builds tools to automatically select the best data on which to train deep learning models. Our tools leverage cutting-edge research—much of which we perform ourselves—to identify redundant, noisy, or otherwise harmful data points. The algorithms that power our tools are modality-agnostic—they’re not limited to text or images—and don’t require labels, making them ideal for realizing the next generation of large deep learning models. Our products allow customers in nearly any vertical to train better models for cheaper.
What they do: Automated AI data curation tools to select, augment, and batch training data for deep-learning models
Headquarters: Redwood City, California, United States
Founding team highlights: Co‑founders include Ari Morcos (CEO), Bogdan Gaza (CTO), Matthew Leavitt (CSO)
Funding: Raised a Seed (~$11.65M) and a $46M Series A (total ≈ $57.5M)
Employees: Approximately 48
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AI training data quality and curation for deep learning models.
Technology, Information and Internet
$11.65M
Seed included participation from Radical Ventures, Conviction Capital, Quiet Capital and prominent angel backers
$46M
Series A led by Viviana Faga and Astasia Myers from Felicis with participation from prior investors and strategic backers
“Backed by top-tier VCs and prominent AI/tech angels (including Jeff Dean, Yann LeCun, Geoffrey Hinton, Adam D'Angelo), indicating strong investor confidence in AI research-driven teams”
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:
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