Datology AI

Datology AI

Product Manager

Redwood City · Staff+

Sponsorship not specified$215k-$300kDetected 99 days ago
API DevelopmentMachine LearningData EngineeringMLOpsProduct ManagementProduct StrategySalesProcurementCustomer SuccessResearchCommunication

About the role

  • This role will shape how Datology evolves from a technically differentiated platform into a category-defining AI tooling company.

Responsibilities

  • Partner with research and engineering to turn ambiguous, early-stage outputs into concrete, shippable product decisions.
  • Define and drive the enterprise product experience -- including platform UX, API design, deployment flexibility (BYOC, on-prem), and integrations with existing ML workflows
  • Develop deep customer intuition by engaging directly with enterprise ML teams, data scientists, and infrastructure engineers -- turning their pain points into a clear product strategy
  • As our first Product Manager, you will own the product strategy and roadmap for our enterprise data curation platform.
  • This is a high-leverage, high-ownership role where you'll build the function from the ground up.
  • You'll partner closely with the founders, our research, engineering teams to define what we build and why. This role will shape how Datology evolves from a technically differentiated platform into a category-defining AI tooling company.
  • Own the product roadmap end-to-end: from discovery and prioritization through launch and iteration, with a focus on enterprise-grade AI tooling
  • You'll partner closely with the founders, our research, engineering teams to define what we build and why.
  • Serve as the connective tissue between research output and commercial product -- helping the team decide what to build, sequence how, and measure whether it's working

Requirements

  • You know the difference between a product that's powerful and one that's actually used

Nice to have

  • Hands-on experience with model training, data pipelines, or MLOps workflows
  • Exposure to enterprise procurement and compliance requirements (BYOC, on-prem, data sovereignty)

Skills

  • Work with Sales and Customer Success to ensure the product enables a repeatable, defensible go-to-market motion
  • Track the competitive landscape across AI tooling, MLOps, and data infrastructure to inform positioning and prioritization
  • Prior experience at an AI infrastructure, developer tools, or data platform company

Compensation

  • At DatologyAI, we are dedicated to rewarding talent with competitive salary and meaningful equity. The salary for this position ranges from $215,000 to $300,000.
  • Starting pay is based on job-related skills, experience, qualifications, and interview performance.
  • 401(k) plan with a generous 4% company match.
  • Annual $2,000 wellness stipend.
  • Annual $1,000 learning and development stipend.
  • Daily lunches and snacks are provided in our office!

Benefits

  • 100% covered health benefits (medical, vision, and dental).
  • 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.
  • Bonus points if you have:
  • Our benefits are built to support your well-being and growth:

Company info

  • 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.
  • 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.
  • This role is based in Redwood City, CA.
  • We are in office 4 days a week.
  • 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.
  • 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.
  • If you're excited about our mission and eager to learn, we want to hear from you!
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This listing is sourced directly from Datology AI's careers page and normalized into a canonical job model.