DevOps Engineer

General Atomics Aeronautical Systems, Inc. (GA-ASI), an affiliate of General Atomics, is a world leader in proven, reliable remotely piloted aircraft and tactical reconnaissance radars, as well as advanced high-resolution surveillance systems.

Under general supervision with limited review, this position independently determines approaches/solutions for the design, development and/or modification of specific programs or projects for enterprise-wide end-user, system level, and data management software applications. Involved in planning of application development and deployment as well as responsible for meeting software compliance standards on specific programs or projects. Evaluates integration of software applications with the overall computing environment; responsible for documentation, testing, maintenance, and software updates. Communicates with domain experts, outside customers, users, and management throughout the software development lifecycle.

DUTIES AND RESPONSIBILITIES:

• Design data pipelines and engineering infrastructure to support enterprise level operationalization
• Work as part of an interdisciplinary team to productionize models for air-to-air and air-to-ground combat operations
• Develop and deploy scalable tools and services for rapid training and inference at the edge
• Identify and evaluate new technologies to improve performance, maintainability, and reliability systems
• Apply robust software engineering best practices to ecosystem, including CI/CD, automation, etc.
• Support stable and repeatable model development, with an emphasis on traceability, version control, adversarial robustness and data security
• Help develop and deploy proof-of-concept machine learning systems to the warfighter
• Communicate with stakeholders to develop roadmaps and implementation schedules

We recognize and appreciate the value and contributions of individuals with diverse backgrounds and experiences and welcome all qualified individuals to apply.

Job Qualifications

• Typically requires a Bachelor's or Master's degree in Computer Science, Engineering, or related field and nine years of related experience.
• Must understand machine learning development concepts, principles, and theory and demonstrate complete understanding and model development and analysis concepts.
• Experience building end-to-end systems focused on productionizing AI/ML technology in a distributed computing environment
• Must possess the ability to understand new concepts quickly and apply them accurately throughout an evolving environment.
• Ability to organize, schedule, and coordinate work phases and, determine the appropriate approach at the task level or, with assistance, at the project level and to provide solutions to a range of complex problems.
• Must have strong communication, computer, documentation, presentation, and interpersonal skills, ability to work independently and as part of a team; and, lead a team of less experienced professional employees on semi-routine tasks.
• Experience using/configuring/maintaining the following technologies:
  • Source code and data control repositories (GIT, SVN, MLFlow, DVC, S3 etc.)
  • Continuous Integration Environment (Jenkins, Gitlab, etc.)
  • Linux and associated technologies (RedHat based)
  • Provisioning tools (Puppet, Ansible, Terraform, etc.)
  • Package managers and associated tools (RPMs, Yum, Pypi, pip, Artifactory, etc.)
  • Hypervisors (VMWare, VirtualBox, QEMU, etc), containers (Docker, Podman, etc), and related tools (Vagrant, Packer, Kubernetes, etc.)
  • Webservers and associated tools (Apache, NGINX, etc)
  • Virtual Desktop Infrastructure (VDI), Desktop as a Service (DAAS), "golden image" creation, and related virtualization technologies
  • Cloud computing infrastructure (AWS, Azure, etc.)
  • CI/CD pipelines and orchestration of distributed AI/ML compute
• Software process automation with popular scripting languages (Python, Bash, Powershell, Ansible)
• Experience developing code in at least one high-level programming language (C#, C , Python, and/or Java)
• Experience developing machine learning models using scikit-learn, Keras, PyTorch, Tensorflow, etc.
• Ability to understand tools used by data scientists and experience with automation of these processes
• Able to work extended hours as required.
• Ability to obtain and maintain DoD security clearance is required.