Full-Time

Software Engineer

Machine Learning

Posted on 2/7/2025

DatologyAI

DatologyAI

11-50 employees

Automated data curation for GenAI training

Compensation Overview

$180k - $250k/yr

Company Does Not Provide H1B Sponsorship

San Carlos, CA, USA

In Person

On-site required; four days per week in-office.

Category
AI & Machine Learning (2)
,
Software Engineering (2)
,
Requirements
  • 4+ years of experience
  • Meaningful experience with leading and building production ML systems and platforms that deliver on major product initiatives
  • Strong belief in the criticality of high-quality data and motivation to work with associated challenges
  • Experience reading, understanding, and implementing ML research papers
  • Proficiency in Python and in the most commonly used tools of the ML & Data Science ecosystem
  • Experience maintaining a high-quality bar for design, correctness, and testing
  • Humble attitude, eagerness to help colleagues, and willingness to do whatever it takes to make the team succeed
  • Own problems end-to-end and willingness to pick up missing knowledge to get the job done
  • Experience conducting open-ended research to improve the quality of collected data and running small scale ML experiments
Responsibilities
  • Architect, build, and deploy the ML systems and services that power our data curation platform
  • Design and implement large-scale data pipelines that curate datasets and make them ready for training cutting-edge models
  • Partner with researchers and engineers to bring new features and research capabilities to our customers
  • Ensure that our systems are reliable, secure, and worthy of our customers' trust

DatologyAI offers automated data curation tools to optimize GenAI training by selecting high-quality, relevant data and removing noisy or harmful data. The core tech analyzes datasets and plugs into existing training pipelines, requiring minimal code changes, and scales from small to petabyte-scale data with usage-based pricing. It differentiates itself with end-to-end automated curation at scale and easy integration, supported by recognized research work and contributions to ImageNet, plus a team with CMU PhD expertise and immigrant-founder VC backing. The goal is to help organizations train better AI models more efficiently and cost-effectively by ensuring high-quality data throughout the training lifecycle.

Company Size

11-50

Company Stage

Series A

Total Funding

$57.7M

Headquarters

Redwood City, California

Founded

2023

Simplify Jobs

Simplify's Take

What believers are saying

  • Raised $46M in 2024 to fuel automated data curation expansion.
  • Founders Alex Morcos, Matthew Leavitt, Bogdan Gaza bring Amazon, Twitter expertise.
  • Plans to grow from 10 to 25 employees by end of 2024.

What critics are saying

  • OpenAI replicates DatologyAI pipelines internally, commoditizing tech by 2025.
  • CleanLab undercuts with 30% lower pricing, stealing healthcare clients in 2026.
  • EU AI Act blocks sales to Europe due to black-box non-compliance in 2026.

What makes DatologyAI unique

  • DatologyAI offers modality-agnostic curation for text, images, video, audio, genomic data.
  • Deploys on-premises or VPC, scaling to petabytes without training code changes.
  • Automatically optimizes batching and augmentation for specific model applications.

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Benefits

Health Insurance

Dental Insurance

Vision Insurance

401(k) Company Match

Unlimited Paid Time Off

Annual Wellness Stipend

Annual Learning and Development Stipend

Relocation Assistance

Company News

SiliconANGLE Media
May 9th, 2024
DatologyAI raises $46M to streamline AI model training data diets

DatologyAI raises $46M to streamline AI model training data diets - SiliconANGLE

DatologyAI
Feb 23rd, 2024
Introducing DatologyAI — Making models better through better data, automatically

Models are what they eat. AI models trained on large-scale datasets have demonstrated jaw-dropping abilities and have the power to transform every aspect of our daily lives, from work to play. This massive leap in capabilities has largely been driven by corresponding increases in the amount of data we train models on, shifting from millions of data points several years ago to billions or trillions of data points today. As a result, these models are a reflection of the data on which they’re train

SiliconANGLE Media
Feb 23rd, 2024
DatologyAI raises $11.65M to automate data curation for more efficient AI training

DatologyAI raises $11.65M to automate data curation for more efficient AI training.

TechCrunch
Feb 22nd, 2024
DatologyAI is building tech to automatically curate AI training datasets | TechCrunch

A new startup, DatologyAI, claims to be able to automatically curate the massive data sets on which AI models train.

INACTIVE