About the role
What we're looking for:
We need someone with deep technical legitimacy in AI/ML who is genuinely X-native and can turn cutting-edge research into compelling narratives, demos, threads, and videos that resonate with a technical audience. You should be comfortable operating at the intersection of engineering and media, with a track record of building recognizable voices and driving organic engagement in the AI community. Bonus points if you have your own audience on X or experience at an AI model/infrastructure company.
What you'll do:
- Turn DatologyAI's research and product work into technical storytelling — threads, demos, videos, and launches that a technical audience finds genuinely interesting
- Build and run a recognizable, native voice for DatologyAI on X day-to-day, including replying, quote-posting, and participating in live conversations in real time
- Help founders and researchers show up in their own voices by drafting and enabling their social presence authentically
- Own end-to-end research launches across X, the technical blog, and video — from the angle and assets to sequencing and follow-through
- Build real relationships with researchers, open-source developers, AI creators, and technical founders in the community
- Bring community feedback back to the product and research teams to inform what gets built and communicated next
- Run experiments across formats and channels, track what earns attention and trust from the right people, and use data to sharpen strategy
About DatologyAI
DatologyAI is building the future of AI training data. The company's core insight is simple but powerful: models are what they eat. A large portion of training compute is wasted on data that is already learned, irrelevant, or even harmful — leading to worse models that cost more to train and deploy.
DatologyAI has built a state-of-the-art data curation suite that automatically curates and optimizes petabytes of data to create the best possible training data for deep learning models. Their algorithms are modality-agnostic (not limited to text or images) and don't require labels, making them ideal for powering the next generation of large-scale AI models.
The results are dramatic:
- 7x–40x faster training depending on the use case
- Model performance improvements as if trained on >10x more raw data without increasing training cost
- Smaller models with fewer than half the parameters outperforming larger models, substantially reducing deployment costs
Founded in 2023, DatologyAI raised a total of $57.5M across a Seed and Series A round. Their 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 of optimizing training data for models.
The company is headquartered in Redwood City, California, operates in-office 4 days a week, and is rapidly scaling — growing from approximately 54 people to 80–90 by end of year as they close out a strong customer pipeline. Their engineering team is approximately 20 people with a flat organizational structure, offering early employees massive ownership and the opportunity to shape how infrastructure and products are built at a critical inflection point in AI.
Required skills
Other roles at DatologyAI
Job details
Salary
$160,000 - $230,000
Location
Redwood City, United States
Experience
5+ years
Funding
Total raised
$57.5M
Last stage
Series A
Investors
Founders
Ari Morcos
CEO
Matthew Leavitt
CSO
Bogdan Gaza
CTO
What happens next.
No applications, no recruiter spam. Just the intro.
Confirm the fit
A few questions to make sure this role is the right shape for you. Two minutes.
I pitch you to the company
I write the intro, send it to the founder, and handle the back-and-forth.
A meeting lands on your calendar
If they’re a yes, I book the chat. You show up — that’s the whole job-hunt.