Full-Time

Product Manager

Updated on 9/10/2026

DatologyAI

DatologyAI

11-50 employees

Automated data curation for GenAI training

Compensation Overview

$215k - $300k/yr

Company Does Not Provide H1B Sponsorship

San Mateo, CA, USA

In Person

Four days in the office per week are required; relocation assistance is available for moves to the Bay Area.

Category
Product (1)
Required Skills
MLOps
Data Science
Product Management
Machine Learning
Data Engineering

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Requirements
  • At least 5 years of product management experience, including at least 3 years building enterprise software or artificial intelligence/machine learning tooling at a senior or staff level.
  • A strong technical foundation, including the ability to read research papers, engage credibly with machine learning engineers about training pipelines and data infrastructure, and distinguish meaningful technical differentiation from noise.
  • Experience shipping products that started as a research paper or prototype and imposing structure while preserving the technology's distinctive qualities.
  • Experience as a founding or early product manager, with a track record of building product functions and processes.
  • Deep familiarity with enterprise artificial intelligence and machine learning buyers, including how machine learning teams evaluate, adopt, and continue using tools and how infrastructure decisions are made.
  • Strong product judgment for developer and technical user experiences.
  • Strong cross-functional communication, including explaining research results to sales teams and translating customer complaints into actionable items for engineers.
  • Comfort operating in ambiguity and a bias toward decisive, data-informed action.
Responsibilities
  • Own the product roadmap end-to-end, from discovery and prioritization through launch and iteration, with a focus on enterprise-grade artificial intelligence tooling.
  • Partner with research and engineering teams to turn ambiguous, early-stage outputs into concrete, shippable product decisions.
  • Define and drive the enterprise product experience, including platform user experience, application programming interface design, deployment flexibility such as bring your own cloud and on-premises deployment, and integrations with existing machine learning workflows.
  • Engage directly with enterprise machine learning teams, data scientists, and infrastructure engineers to develop customer intuition and turn pain points into product strategy.
  • Build foundational product-management infrastructure, including discovery frameworks, roadmap tooling, release processes, and cross-functional rituals that scale as the team grows.
  • Work with Sales and Customer Success to ensure the product enables a repeatable, defensible go-to-market motion.
  • Track the competitive landscape across artificial intelligence tooling, machine learning operations, and data infrastructure to inform positioning and prioritization.
  • Connect research output with the commercial product by helping the team decide what to build, sequence work, and measure whether it is working.
Desired Qualifications
  • Hands-on experience with model training, data pipelines, or machine learning operations workflows.
  • Prior experience at an artificial intelligence infrastructure, developer tools, or data platform company.
  • Exposure to enterprise procurement and compliance requirements, including bring your own cloud, on-premises deployment, and data sovereignty.

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

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Simplify Jobs

Simplify's Take

What believers are saying

  • DatologyAI raised $46M in May 2024, giving runway for aggressive hiring.
  • 2026 partnerships with Thomson Reuters and Arcee validate enterprise demand immediately.
  • Thomson Reuters launched Thomson-1.0 using DatologyAI-curated data, proving commercial impact.

What critics are saying

  • OpenAI, Anthropic, and Databricks bundle data tooling, crushing standalone pricing.
  • If Thomson Reuters and Arcee internalize curation, DatologyAI loses repeatable revenue by 2027.
  • A weak benchmark year would kill its claim that curated data beats scaling laws.

What makes DatologyAI unique

  • DatologyAI curates training data, not models, for faster mid-training and post-training.
  • Thomson Reuters used DatologyAI to build a 100B-token legal dataset in 2026.
  • Arcee AI credits DatologyAI with curated 17T public tokens for Trinity-Large.

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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.