Apply machine learning, statistics, to develop algorithms to solve challenging problems
Leverage strong foundation in machine learning, data science, and signal processing to solve complex challenges in the RF domain
Design and build data pipelines, including ETL processes, data warehousing solutions, and optimizing workflows for large-scale data processing
Hands-on experience with cloud-based infrastructure 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 and ML libraries
Establish ML governance practices, including version control for datasets and models, experiment tracking, model monitoring, implementing reproducible research principles
Requirements
Master’s degree in quantitative field with mathematical underpinnings
At least 5 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
Must have active Top Secret Clearance with the ability to obtain SCI with Polygraph
Ph.D. in computer science, computer engineering, or machine learning, Statistics, applied mathematics or Physics (Desired)
Experience applying machine learning to signal processing and/or other time-series data analysis applications (Desired)