AI/ML Systems Engineer
Tasks
- Analyze ground segment architectures and standards
- Apply agentic AI for architecture trade studies
- Create technical documentation for architectural diagrams and interfaces
- Define architectural principles standards and guidelines
- Define human in the loop validation governance and traceability
- Deliver architecture recommendations and AI ML implementation roadmaps
- Design secure auditable AI ML workflows
- Develop AI ML approaches for engineering data analysis
- Develop and document Government Reference Architecture
- Establish reusable AI ML enabled systems engineering practices
- Evaluate AI ML and MLOps technologies for ground environments
- Improve CI CD and DevSecOps pipelines with AI automation
- Lead AI ML enabled engineering in architecture workflows
- Support ground systems architecture development and integration planning
- Translate user needs into reference architecture
Perks/Benefits
- N/A
Skills/Tech-stack
AI Assurance | AI Governance | Agentic Workflows | Architecture Modeling | Architecture development | Artifact Repositories | Artificial Intelligence | CI/CD | Cameo Systems Modeler | Cloud Computing | Containers | Data analytics | DevSecOps | Enterprise Architect | GitLab | Interface definition | Jenkins | Kubernetes | Language Models | Large Language Models | MLOps | Machine Learning | MagicDraw | Mbse | Pipeline observability | Prompt engineering | Requirements Traceability | Retrieval-Augmented Generation | Risk Analysis | Systems Modeler | Systems engineering | Technical documentation | Test automation
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI/ML Systems Engineer | Engineer | ML Systems Engineer | Systems Engineer
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