Base Salary
$149k - $311k/yr
Responsibilities
- Design, develop, and maintain automated deployment pipelines for lowside and highside products.
- Adapt application code to improve compatibility and integration with automated deployment environments.
- Contribute to deployment-system architecture and design to improve efficiency and reliability.
- Troubleshoot and resolve complex deployment issues with minimal disruption to development cycles.
- Develop understanding of product and ML architectures to support seamless integration and deployment.
- Document pipeline processes and configurations for maintainability and knowledge transfer.
- Incorporate security best practices throughout the deployment pipeline and development processes.
- Drive standardization and collaboration across product teams toward a unified SDLC.
Requirements
- Active TS/SCI clearance and the ability and willingness to obtain a CI Poly are required.
- 2–3 years of experience as a DevOps Engineer, DevSecOps Engineer, CI/CD-focused Software Engineer, or similar.
- Demonstrated experience building or significantly enhancing automated deployment pipelines.
- Experience configuring and adapting application code for evolving CI/CD environments.
- Experience with containerization and deployment technologies such as Kubernetes, Terraform, and Docker.
- Familiarity with AWS, Azure, or GCP cloud platforms.
- Strong scripting and automation proficiency with Python, Bash, or PowerShell.
- Familiarity with Jenkins, GitLab CI, GitHub Actions, or Azure DevOps.
- Knowledge of software architecture, system design, and version control systems.
- Understanding of software-development security best practices and interest in integrating ML components into automated workflows.
- Strong problem-solving, analytical, collaboration, and communication skills.
- Exposure to ML lifecycles or MLOps concepts and prior classified-environment experience are preferred.
Benefits
- Full-time role with base salary, equity eligibility, comprehensive health, dental and vision coverage, retirement benefits, learning and development stipend, and generous PTO.
- The role may include a commuter stipend and is associated with listed locations including San Francisco, New York, Seattle, Hawaii, Washington DC, Texas, Colorado, and St. Louis.
- Compensation and location eligibility are determined based on work location, skills, experience, qualifications, interview performance, and education or training.
Tech Stack
Categories
About Scale AI
Scale’s mission is to develop reliable AI systems for the world’s most important decisions. We provide the high-quality data and full-stack technologies that power the world’s leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. The Scale Generative AI Platform allows customers to build, evaluate, and control advanced AI agents and applications that continuously improve. The Scale Data Engine provides the technology to collect, curate, and annotate high-quality datasets. Through our Scale Labs, we test models with rigorous benchmarks and novel research to ensure breakthroughs translate into systems people can trust. Scale powers the most advanced LLMs and generative models in the world through RLHF, data generation and model evaluation. We work with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force.