Scale AI

Field Engineer, Data Engine

Scale AI
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2 months ago
St. Louis, MO, USA or Washington, DC, USAMid Level
H1B sponsor

Base Salary

$140k - $290k/yr

Responsibilities

  • Define and execute the vision for data pipelines and agents with cross-functional teams.
  • Implement end-to-end data integrations that synchronize customer data with Scale’s platform.
  • Deploy and maintain Scale software at customer sites.
  • Develop customer-requested features and backend systems that can operate as standalone products.
  • Participate in customer engagements to understand requirements and deliver onsite technical solutions.

Requirements

  • Knowledge of ETL processes, data pipelines, data modeling, data warehousing, and data governance.
  • Experience as a hybrid customer-facing, forward-deployed software engineer who can adapt to different roles.
  • Prior experience developing with Python.
  • Familiarity with AWS, Azure, or GCP and cloud-native application deployment.
  • Understanding of Docker, Kubernetes, Linux, shell scripting, operating systems, and networking technologies is preferred or beneficial.
  • Strong analytical, problem-solving, critical-thinking, and root-cause analysis skills.
  • Active Secret security clearance and willingness to obtain a TS/SCI clearance.
  • Willingness to work more than 50% onsite in a secured space.

Benefits

  • Comprehensive health, dental, and vision coverage.
  • Retirement benefits, learning and development stipend, and generous paid time off.
  • Potential commuter stipend.
  • Full-time role with more than 50% onsite work in a secured customer environment.
  • Eligible roles may include equity-based compensation.
Scale AI

About Scale AI

5,001-10,000 employees

Scale AI builds data annotation services and AI development tools for enterprises and government agencies, sold as a platform and managed services. Its products include the Scale Generative AI Platform for building and evaluating agents and the Data Engine for collecting, curating, and labeling training data, including RLHF and model evaluation. Founded in 2016 and headquartered in San Francisco, the company is privately held and works across domains from computer vision to LLM applications.

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