Apply machine learning, statistics, to develop algorithms
Solve challenging problems, signal processing, and computer networking domains
Leverage strong foundation in machine learning, data science, and signal processing to solve complex challenges in the RF domain.
Proficiency in designing and building data pipelines, including experience with ETL processes and data warehousing solutions
Hands-on experience with cloud-based infrastructure (e.g., AWS, Azure, GCP) for deploying ML solutions, including containerization, orchestration, and CI/CD pipelines for model deployment
Programming expertise in Python and SQL, with experience using data engineering frameworks (e.g., Spark, Airflow) and ML libraries (e.g., TensorFlow, PyTorch, scikit-learn)
Establish ML governance practices, including version control for datasets and models

Requirements

Master’s degree in quantitative field with mathematical underpinnings and at least 4 years’ experience
Experience developing models
Strong background in machine learning, mathematics and statistics
Comfortable using Linux operating systems and commonly used Linux utilities
Must be a US Citizen with the ability to obtain, maintain and/or transfer the required security clearance as dictated by the contract
Must have active Top Secret Clearance.
Desired: Ph.D. in computer science, computer engineering, or machine learning, Statistics, applied mathematics or Physics
Experience applying machine learning to signal processing and/or other time-series data analysis applications
Knowledge of or experience with information theory, probability theory, parametric and non-parametric statistical tests
Familiarity with concepts and techniques associated with adversarial AI and AI/ML assurance.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningstatisticsdata sciencesignal processingdata pipelinesETL processesdata warehousingPythonSQLLinux

Certifications

Top Secret Clearance