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DatologyAI
DatologyAI
1 – 10 Employees
Artificial Intelligence
DatologyAI develops tools that help teams choose better training data for deep learning models. Its research-driven algorithms identify redundant, noisy, or harmful examples and work across data types without requiring labels. The company’s products support organizations seeking to improve model quality while reducing training costs, and its work sits at the intersection of artificial intelligence research and data curation.
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Senior Infrastructure Software Engineer

Build secure, scalable multi-cloud and machine learning infrastructure for DatologyAI’s data curation platform. Support the tooling, training, and inference systems behind its products.

USUnited StatesCACalifornia
$180,000 – $300,000 / year
HybridFull-timeMiddleSeniorEnglish RequiredInfrastructure Engineer
AWSAzureCloudGoogle Cloud PlatformKubernetesPythonTerraform

Description

  • Build development and production platforms that power DatologyAI products
  • Improve reliability and security as systems scale
  • Architect, build, and deploy core infrastructure across cloud providers and deployment models
  • Increase company productivity with effective tools and systems
  • Work with researchers and engineers to deliver new features and research capabilities to customers
  • Make business-critical technical decisions and help guide product direction
  • Lead data infrastructure development, including multi-cloud support, deployment models, and training and inference infrastructure

Requirements

  • At least four years of relevant experience
  • Substantial experience leading and building large-scale infrastructure
  • Proficiency in Bash, Kubernetes, Python, Terraform, or comparable technologies
  • Experience with AWS, Azure, Google Cloud Platform, or on-premises environments
  • Ability to debug issues across the stack, including networking, performance, hardware, and memory leaks
  • Experience building and operating scalable, reliable, and secure systems
  • Experience building data infrastructure from the ground up, or nearly so, at a fast-growing startup is preferred
  • Experience building machine learning or deep learning infrastructure, or data infrastructure that feeds training for large ML models, is preferred
  • A humble, helpful approach and willingness to contribute to the team’s success
  • Ability to own problems end to end and learn what is needed to solve them

Benefits

  • Medical, vision, and dental coverage paid in full
  • 401(k) plan with a 4% company match
  • Unlimited paid time off
  • 12 weeks of paid parental leave
  • Six months of work-from-home flexibility
  • Annual $2,000 wellness stipend
  • Annual $1,000 learning and development stipend
  • Daily office lunches and snacks
  • Relocation assistance for employees moving to the Bay Area
  • Equity

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