Global InfoTek, Inc.

Network Engineer

• Performs all systems integration work, system management and configuration, operation, testing, and reset of MACC-TTE virtual and physical environments
• Configures and deploys virtual and physical servers, workstations, and small processor-controlled devices
• Actively supports information assurance (IA) requirements
• Responsible for installing, configuring, upgrading, patching, troubleshooting, and maintaining hardware, software, and server configurations to ensure confidentiality, integrity, and availability
• Manages accounts, firewalls, access controls, passwords, account creations, and conducts administration
• Provides routine automation, maintains security policies, trains, or offers technical support
• Maintains the platform's uptime, performance, resources, and availability
• Creates automation scripts using Bash, Python, or Ansible to streamline processes
• Builds, configures, and maintains virtual environments

Senior Network Engineer II

• Leads all technical efforts concerning planning, development, implementation, problem resolution, and administration of MACC-TTE networks
• Serves as the primary technical expert regarding network system policy and short/long-range planning
• Defines future roadmaps and makes strategic recommendations based on alternative analyses

Senior Network Engineer III

Full-stack Engineer

• Implement, test, and maintain assigned pipeline components
• Develop and maintain browser-based visualization and reporting tools
• Implement and maintain stream simulation infrastructure
• Develop lightweight TNS simulator components
• Contribute to database integration work
• Write comprehensive unit and integration tests for assigned components
• Perform basic Linux system administration on remote servers
• Manage source code using GitLab
• Produce clear technical documentation for implemented components
• Participate in periodic technical check-ins with the program technical lead

Senior Radio Frequency Software Engineer

• Support Cyber Operations Research and Development as the technical lead for production software development
• Own the architecture, implementation, and delivery of the production pipeline
• Lead a team of Senior Software Engineers in support of real world cyber operations
• Establish and maintain disciplined software engineering practices
• Collaborate with the program technical lead to translate research findings into production pipeline components

Principal Radio Frequency Software Engineer

Data Scientist

• Responsible for researching, developing, architecting, and integrating ML models, algorithms, tools, and techniques.
• Analyze large datasets with preprocessing data skills, data cleansing, and conducting data integrity and validation actions.
• Design, develop, and integrate ML models and algorithms to detect AI-generated and manipulated imagery, or for pattern recognition.
• Collaborate with internal teams and external partners to support integration and testing.
• Generate technical reports, visualizations, and summaries suitable for stakeholders.
• Participate in project-wide reviews of requirements, system architecture, and detailed design documents.

Data Scientist / AI/ML Engineer, Imagery

• Implement, test, and maintain assigned pipeline components including stream ingestion, rollup processing, database write, and batch post-processing modules in support of real world cyber operations
• Develop and maintain browser-based visualization and reporting tools (track plots, waterfall displays, SmartBook report generation) that consume pipeline database output
• Implement and maintain stream simulation infrastructure, including TDMA network mission log replay and stream generation at controllable rates for pipeline testing
• Manage source code using GitLab; follow disciplined versioning, branching, and code review practices as established by the Principal Engineer
• Write comprehensive unit and integration tests for assigned components; implement and maintain CI/CD pipelines using GitLab to ensure functionality on hardware or in cloud environment
• Produce clear technical documentation for implemented components including interface specifications, configuration guides, and test procedures.

Lead Radio Frequency Software Engineer

Research Scientist

• Conduct independent, hands-on data analysis on RF sensor datasets using Python and Jupyter notebooks
• Provide technical advice and research direction across a multidisciplinary team
• Serve as primary technical advisor to the government sponsor
• Design and execute analytical investigations into RF sensor data quality
• Produce technical documentation that accurately represents the scope and confidence level of analytical results

Principal Scientist – AI/ML Specialization

Machine Learning Engineer

• Design, build, and validate machine learning models for RF emitter identification — including feature engineering from sensor data, training pipeline development, model evaluation, and iterative refinement based on results
• Conduct hands-on exploratory data analysis on RF sensor datasets using Python and Jupyter notebooks — writing and running analytical code, characterizing feature distributions, identifying data quality issues, and producing documented findings
• Implement and maintain ML data pipelines — ingesting NDF sensor streams, applying rollup and preprocessing logic, constructing training datasets, and ensuring pipeline correctness on constrained edge hardware with no cloud dependency
• Collaborate with the technical lead and Principal AI/ML Engineer to investigate RF sensor data quality, attribution reliability, and feature behavior under contention — writing code to characterize error sources, validate assumptions, and reproduce findings
• Produce clear technical documentation of experiments, model configurations, and results — maintaining reproducibility through disciplined versioning, and contributing to monthly status reports and team knowledge sharing

Senior AI/ML Engineer

• Researching, developing, architecting, and integrating ML models, algorithms, tools, and techniques into existing or new environments
• Analyzing large datasets with preprocessing data skills, data cleansing, and conducting data integrity and validation actions
• Designing, developing, and integrating ML models and algorithms to address specific problems, such as detection of AI-generated and manipulated imagery and video
• Introducing ML and pattern recognition to discover hidden insights
• Collaborating well with a strong lean-forward attitude to shift knowledge left, deliver well, and produce quality results
• Integrating advanced algorithms developed by academic partners into operational workflows using NGA data and environments
• Adapting and optimizing models for real-world conditions (compression, noise, format variability)
• Working with containerized solutions (Docker or similar) to support deployment and reproducibility
• Generating technical reports, visualizations, and summaries suitable for NGA stakeholders
• Participating in technical meetings and reviews within secure environments (SCIF)