Senior DevSecOps Engineer

Job Summary

General Atomics Aeronautical Systems, Inc. (GA-ASI) is a leader in remotely piloted aircraft and tactical reconnaissance radars. This position designs, develops, and modifies software applications for enterprise-wide end-user, system level, and data management software.

DUTIES & RESPONSIBILITIES

• Design data pipelines and AI/ML engineering infrastructure to support enterprise level operationalization of machine learning systems
• Work as part of an interdisciplinary team to productionize AI/ML models for air-to-air and air-to-ground combat operations
• Develop and deploy scalable tools and services for rapid AI/ML training and inference at the edge
• Identify and evaluate new technologies to improve performance, maintainability, and reliability of machine learning systems
• Apply robust software engineering best practices to machine learning 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

Job Qualifications

• Typically requires a bachelor's degree, master's degree or PhD in computer science, information systems or a related discipline and progressive software development experience as follows; four or more years of experience with a bachelor's degree or two or more years of experience with a master's degree.
• May substitute equivalent experience in lieu of education.
• Must understand software development concepts, principles, and theory and demonstrate complete understanding and application of programming and analysis concepts.
• 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.
• Able 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.
• 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)
  • 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.
• Able to work extended hours as required.
• Ability to obtain and maintain DoD security clearance is required.