---
title: 'Software Engineer, Infrastructure at DatologyAI'
canonical: 'https://feeny.ai/job/software-engineer-infrastructure-datologyai-san-mateo-27yxqv5jp2gv'
type: 'job'
last_seen: '2026-09-05'
---

# Software Engineer, Infrastructure at DatologyAI

- **Company:** DatologyAI
- **Location:** San Mateo, CA
- **Employment:** full-time
- **Posted:** 2025-03-20
- **Last confirmed live:** 2026-09-05
- **Apply:** https://jobs.ashbyhq.com/datologyai/a61a442c-e640-4542-be68-984f99369ec5

## 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

We're looking for an experienced Infrastructure Engineer to join as a member of our core Datology AI team. As one of our early senior hires, you will partner closely with our founders on the direction of our product and drive business-critical technical decisions. You will lead the development of our data infrastructure capabilities, including multi-cloud support and support for various deployment models, as well as training and inference infrastructure. You will have a broad impact on the technology, product, and our company's culture.

## WHAT YOU'LL WORK ON

- Design and build the development and production platforms that power our products, enabling reliability and security at scale
- Architect, build, and deploy our core infrastructure while supporting multiple cloud providers and various deployment models
- Accelerate company productivity by empowering your fellow engineers & teammates with excellent tooling and systems, providing a best-in-case experience
- Partner with researchers and engineers to bring new features and research capabilities to our customers

## ABOUT YOU

- 4+ years of relevant experience
- Have meaningful experience in spearheading and constructing large-scale infrastructure
- Proficiency in bash, Kubernetes, Python, and/or Terraform or similar technologies
- Have experience working with AWS, other cloud platforms such as Azure or GCP and/or on-prem environments
- Have expertise in debugging problems across the stack, such as networking issues, performance problems, hardware issues or memory leaks
- Take pride in building and operating scalable, reliable, secure systems
- Have a humble attitude, an eagerness to help your colleagues, and a desire to do whatever it takes to make the team succeed
- Own problems end-to-end and are willing to pick up whatever knowledge you're missing to get the job done

We would love it if you had:

- Built out data infrastructure from, or nearly from, scratch at a fast-growing startup.
- Experience building ML/DL infrastructure and/or data infrastructure that feeds into training large ML models

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 competitive salary and meaningful equity. The salary for this position ranges from $180,000 to $300,000.

- Starting pay is 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)

## Other roles at DatologyAI

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