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Scale AI

Supplies AI training data and builds AI apps

DevOps Engineer, Public Sector - Infrastructure & Security

DevOps EngineeringConfirmed live in the last 24 hours
Full-timeWashington, DC, USAIn-person

About the Job

Requirements

  • At least an active Top Secret/Sensitive Compartmented Information clearance and the ability and willingness to obtain a counterintelligence polygraph are required; candidates without at least an active Top Secret/Sensitive Compartmented Information clearance will not be considered.
  • Two to three years of experience as a DevOps Engineer, DevSecOps Engineer, Software Engineer focused on continuous integration and continuous delivery, or in a similar role is ideally desired.
  • A proven track record of building or significantly enhancing continuous integration and continuous delivery pipelines is desired.
  • Experience configuring and adapting application code to integrate with evolving continuous integration and continuous delivery environments is desired.
  • Experience working with containerization and deployment technologies such as Kubernetes, Terraform, and Docker is desired.
  • Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform is desired.
  • Strong proficiency in scripting and automation, such as Python, Bash, or PowerShell, is desired.
  • Familiarity with continuous integration and continuous delivery platforms such as Jenkins, GitLab CI, GitHub Actions, or Azure DevOps is desired.
  • Knowledge of software architecture, system design, and version control systems is desired.
  • Basic understanding of software development security best practices and eagerness to integrate them is desired.
  • Experience with containerization technologies such as Docker or Kubernetes is a nice-to-have.
  • Exposure to machine learning lifecycles or MLOps concepts is a nice-to-have.
  • Prior experience in classified environments is a nice-to-have.

Responsibilities

  • Design, develop, and maintain robust continuous integration and continuous delivery pipelines to automate deployment of lowside and highside products.
  • Collaborate with product and engineering teams to enhance application code for improved compatibility and integration within automated pipelines.
  • Contribute to the architecture and design of deployment systems to improve efficiency and reliability.
  • Troubleshoot and resolve complex deployment issues to minimize disruption to development cycles.
  • Develop an understanding of product and machine learning architectures to facilitate integration and deployment.
  • Document pipeline processes and configurations to support maintainability and knowledge transfer.
  • Incorporate security best practices into all stages of the continuous integration and continuous delivery pipeline.
  • Drive standardization and collaboration across product teams to create a unified and efficient software development life cycle.

Desired Qualifications

  • Comfort with rapidly changing, fast-paced environments and a passion for finding automated solutions to complex problems are desired.
  • A hunger for learning new technologies, particularly integrating machine learning into automated workflows, is desired.
  • Strong problem-solving and analytical abilities are desired.

About the Company

Scale AI

Supplies AI training data and builds AI apps

Scale AI supplies the data that AI labs use to train and test their models, and it builds custom AI applications for companies and government agencies such as the Pentagon. It first made its name labeling camera and sensor data for self-driving car companies like Waymo, then worked with OpenAI on InstructGPT, the 2022 forerunner of ChatGPT. Freelancers, some of them doctors and lawyers, write, label, and grade examples through its Outlier platform, and labs pay Scale for this data and for tests of model quality. Clients pay Scale to build AI tools on their own data, and some of those tools run on classified military networks. Alexandr Wang and Lucy Guo founded Scale AI in 2016, and it is based in San Francisco.

Company size
1,001-5,000
Company stage
Acquired
Total funding
$1.6B
Headquarters
San Francisco, CA
Founded
2016

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