---
title: 'AI Developer Experience & Media Lead at DatologyAI'
canonical: 'https://feeny.ai/job/ai-developer-experience-media-lead-datologyai-san-mateo-pf7jfn1t6ad9'
type: 'job'
last_seen: '2026-09-12'
---

# AI Developer Experience & Media Lead at DatologyAI

- **Company:** DatologyAI
- **Location:** San Mateo, CA
- **Employment:** full-time
- **Posted:** 2026-08-04
- **Last confirmed live:** 2026-09-12
- **Apply:** https://jobs.ashbyhq.com/datologyai/4088fa05-de51-45ac-a7bf-fd8fafd8cb5a

## Job description

## 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 research on synthetic data scaling ([BeyondWeb](https://www.datologyai.com/blog/beyondweb)) and pretraining with domain-specific data ([The Finetuner’s Fallacy](https://www.datologyai.com/blog/finetuners-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.

This role is based in San Mateo, CA. We are in office 4 days a week.

## About the Role

In this role, you'll be our expert on social, the person who knows how to make DatologyAI's research travel on X and across the AI community. You'll turn our research into narratives, demos, threads, videos, and launches, build a voice on X that people recognize and trust, and take part in the conversation as it happens. You'll also help our founders and researchers communicate in their own voices. The work sits where engineering meets media. You can read one of our results, understand why it matters, and build a demo or write a thread that a technical audience respects. You have a creator's instincts for hooks, video, distribution, and taste. And you're genuinely active in the AI community on X, replying, experimenting, and engaging, not just posting announcements. You'll build the playbook as you operate it. We have real research worth talking about, credible founders, and an audience that's already here, and we're looking for someone who can meet them where they are and be trusted to run with it.

## What You'll Work On

- Technical storytelling and demos. Take our research and product work and turn it into narratives, threads, videos, live demos, and launches that a technical audience finds genuinely interesting.
- Company voice on X. Build a recognizable, native voice for DatologyAI on X and run it day to day. Reply, quote-post, and participate in live conversations in real time.
- Founder and researcher enablement. Help leadership and our research team show up in their own voices.
- Research launches, end to end. Own the public launch of our research across X, the technical blog, and video: the angle, the assets, the sequencing, and the follow-through, so each result gets the attention it deserves.
- Community and relationships. Build real relationships with researchers, open-source developers, AI creators, and technical founders.
- Feedback loop into product and research. Bring what you learn in the community back to the team, so what we hear from developers and researchers informs what we build and what we say next.
- Experiments and measurement. Run experiments across X, technical writing, video, launches, and events. Track what earns attention and trust from the right people, and use it to sharpen what we do next.

## About You

- Technical legitimacy. You can build and explain real AI systems. You can read a paper or a launch brief, understand it, comment on it accurately, and produce a demo or a technically serious thread from it.
- X-native. You genuinely live on the platform. You post and reply frequently, participate in live conversations, and have a native tone. We care far more about your reply and quote-post behavior and your taste than your follower count.
- Creator instincts. You understand hooks, compression, video, personality, and distribution. You have a recognizable voice and a feel for what makes people stop scrolling and engage.
- Ambient participant, not a broadcaster. You interact, experiment, and joke in the conversation rather than only publishing polished company announcements.
- Able to write in other voices. You can help a founder or researcher sound like themselves, credibly, without flattening what makes them distinctive.
- Self-starter with a bias toward action. You take an objective, build the approach, and run with it.
- Startup-ready. Comfortable building the playbook as you operate it, moving fast, and owning outcomes end to end.

## Nice to Have

- Your own audience on X, or a track record of building one, with side projects or demos that have circulated organically
- Experience at an AI model or infrastructure company, or in developer relations, developer marketing, or growth engineering
- A body of technical content spanning agents, inference, multimodality, coding workflows, or similar
- Comfort in front of a camera and the ability to produce short technical video

Don't meet every single requirement? We still encourage you to apply. If you're excited about our mission and eager to learn, we want to hear from you!

## Compensation

At DatologyAI, we are dedicated to rewarding talent with a highly competitive salary and significant equity. The base salary range for this position is 160,000 - $230,000.

- The candidate's starting pay will be determined based on job-related skills, experience, qualifications, and interview performance.

Benefits:

- 100% covered health benefits (medical, vision, and dental).
- 401(k) plan with a generous 4% company match.
- Unlimited PTO policy
- Paid Parental Leave of 12 weeks, plus 6 months of WFH flexibility.
- Annual $2,000 wellness stipend.
- Annual $1,000 learning and development stipend.
- Daily lunches and snacks are provided in our office!
- Relocation assistance for employees moving to the Bay Area.

## About DatologyAI

## Company Overview
- **One-liner**: DatologyAI provides an automated platform that curates training data for deep learning models, helping companies train better AI models faster and more cost-effectively.
- **Entity Type**: Private (Series A)
- **Headquarters**: Redwood City, California, United States
- **Founded**: 2023
- **Founders**: Ari Morcos (CEO), Bogdan Gaza (CTO), Matthew Leavitt

## Core Business
- **Primary industry/industries**: Artificial intelligence, Machine learning infrastructure, Data curation
- **Target customers**: B2B — Enterprises and AI teams training large-scale deep learning models across verticals
- **Mission or purpose statement**: "Democratize AI data curation, allowing every company to easily train its own custom model on the right data without needing to invest massive resources." [datologyai.com](https://www.datologyai.com/about)

## Products & Services
- **DatologyAI Platform**: A fully automated, scalable data curation platform that identifies redundant, noisy, or harmful data points in training datasets. It integrates with existing infrastructure (from blob storage to dataloader), is modality-agnostic (works for text, images, etc.), and requires no labels. The goal is to optimize training efficiency, maximize model performance, and reduce compute costs. [datologyai.com](https://www.datologyai.com/about)

## Market Standing
- **Valuation/Market Cap**: Not publicly available
- **Key Metric**: Total funding of $57.65M [cbinsights.com](https://www.cbinsights.com/company/datologyai)
- **Notable Investors/Partners**: M12 (Microsoft’s venture fund), Amplify Partners, Amazon Alexa Fund [datologyai.com](https://www.datologyai.com/about)
- **Growth Signals**: Founded in 2023 and already raised $57.65M (including a $46M Series A in 2024); backed by top-tier investors; founded by researchers with backgrounds at DeepMind, Meta AI (FAIR), and MosaicML (acquired by Databricks); cutting-edge research (80% novel and unpublished) directly powers the product.

## Competitive Advantages
- **Research-driven product**: The platform is built on frontier research in data curation for deep learning, with the team publishing novel techniques at top conferences (NeurIPS, ICLR).
- **Modality-agnostic & label-free**: Works across data types and doesn’t require labeled data, making it applicable to a wide range of use cases.
- **Deep technical team**: Founders bring expertise from leading AI labs (DeepMind, Meta AI, MosaicML) and large-scale infrastructure experience (Amazon, Twitter).
- **Customer-obsessed and scalable**: Designed to be easy to implement and generalize across models, directly reducing compute costs for customers.

## Strategic Focus
- **Product & research**: Continue to push the boundaries of data curation research and deploy it directly into the product to improve model efficiency and capability.
- **Customer success**: Deeply focus on customer problems and goals to drive adoption and success.
- **Scaling the team**: Actively hiring across engineering, research, sales, and product roles to grow the organization.

## Why Work Here
- **Impactful mission**: Solve the "biggest problem in AI model training" — data quality — with research that has real-world impact.
- **World-class team**: Work alongside researchers and engineers from DeepMind, Meta AI, and MosaicML.
- **Culture of research**: Engineering and research are deeply intertwined; ideas are deployed into production, not just published.
- **In-office culture**: HQ in Redwood City, CA, with a strong in-office expectation ("In-Office" listed for all roles on Built In). [builtin.com](https://builtin.com/company/datologyai)
- **Benefits**: 100% covered health benefits (medical, vision, dental), 401(k) with 4% match, unlimited PTO, $2,000 annual wellness stipend, $1,000 annual L&D stipend, daily lunch/snacks, dinner for late work, relocation assistance. [datologyai.com](https://www.datologyai.com/careers)
- **Fast-paced, high-growth environment**: A chance to grow fast and make a significant impact at a well-funded startup.

## Sources
1. [DatologyAI About Page](https://www.datologyai.com/about)
2. [DatologyAI Careers Page](https://www.datologyai.com/careers)
3. [Built In Company Profile](https://builtin.com/company/datologyai)
4. [CB Insights Company Profile](https://www.cbinsights.com/company/datologyai)
5. [LinkedIn Company Page](https://www.linkedin.com/company/datologyai)

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