We are excited to announce an opening for a DevOps Engineer to join the Research and Development division of a client in Colorado Springs, CO. This role will support teams working on advanced AI/ML applications in missile defense, battle management, and related domains. In this role, you will help deploy, scale, and standardize machine learning development workflows in support of Small Business Innovation Research (SBIR) and Small Business Technology Transfer (STTR) projects.
You’ll work at the intersection of infrastructure, software engineering, and machine learning—enabling high-performing research teams to deliver impactful, secure, and maintainable solutions.
Responsibilities
As a DevOps Engineer, you will architect, implement, and maintain modern ML development pipelines while collaborating across multiple research teams to ensure they can develop, test, and deploy machine learning capabilities quickly and securely.
You will:
- Build and maintain GPU-capable development environments and containerized workflows.
- Develop CI/CD pipelines (e.g., GitLab CI) with automated testing, linting, and deployment.
- Implement and enforce merge request policies and code quality standards.
- Create shell scripts and configuration files to streamline setup, reproducibility, and remote development (e.g., SSH-based HPC access).
- Define and document standardized ML development practices across teams.
- Collaborate with ML researchers, software engineers, and cybersecurity teams to transition prototypes into production-ready systems.
- Support secure deployment of ML solutions in DoD-restricted environments.
- Contribute to SBIR/STTR project execution and proposal development.
Basic Qualifications
- Bachelor’s degree in computer science or a related technical field.
- 4+ years of experience in DevOps, including support for GPU-accelerated workloads.
- U.S. citizenship and the ability to obtain a Secret security clearance.
(Candidates must meet all basic qualifications to be considered.)
Preferred Qualifications
- Proficiency in Linux-based development, shell scripting (Bash), and remote development on GPU-accelerated hardware.
- Hands-on experience with containerization and reproducibility using Podman (or similar) and tools like Conda, Poetry, or Pixi, including setup behind proxies and secure artifact repositories.
- Proven ability to build and manage CI/CD pipelines in GitLab (or equivalent), including automated testing, MR enforcement, and runner configuration.
- Familiarity with Python-based machine learning frameworks and tooling (e.g., PyTorch Lightning, Optuna, MLflow, Ray-RLLib).
- Experience deploying ML solutions in secure, classified, or DoD-restricted environments.
- Knowledge of infrastructure-as-code tools (e.g., Terraform, Ansible) and DevSecOps best practices.
- Understanding of software supply chain security, including artifact validation and SBOMs.
- Strong communication skills with the ability to write clear technical documentation and support onboarding across technical teams.
