Radio Frequency Machine Learning (RFML) Product Workflow Engineer, Secret Clearance Eligible

Blue Sky Innovators•Reston, VA

About The Position

Blue Sky Innovators is seeking an undergraduate student or recent graduate to join our RF Machine Learning team as an RFML Product Workflow Engineer. This role offers a unique opportunity to architect and implement the complete data pipeline from raw RF signal ingestion through machine learning-based identification and fingerprinting. You'll work at the intersection of signal processing, machine learning, and software engineering to build production-grade systems that advance the state-of-the-art in RF domain analysis.

Requirements

Currently pursuing or recently completed a BS/BA in Computer Science, Software Engineering, or related field
Strong programming skills in Python with experience in software design patterns
Understanding of data structures and algorithms
Experience with version control (Git) and collaborative development workflows
Ability to read technical documentation and learn new technologies independently
Strong problem-solving skills and attention to detail
Due to the nature of the work, you must be eligible for a security clearance and must be a U.S. Citizen.

Nice To Haves

Coursework or projects in machine learning, signal processing, or data engineering
Experience with scientific Python libraries (NumPy, SciPy, pandas)
Familiarity with ML frameworks (PyTorch, TensorFlow)
Knowledge of database systems (SQL, vector databases, or time-series databases)
Experience with containerization (Docker) and orchestration tools
Understanding of RF fundamentals or digital signal processing concepts
Experience with package managers and virtual environments (conda, uv, pip)
Familiarity with configuration management and experiment tracking tools

Responsibilities

Design and implement end-to-end data workflows from raw IQ data ingestion through RFML model inference
Build robust data processing pipelines that handle various RF signal formats (SIGMF, raw IQ files, etc.)
Architect scalable fingerprinting systems that extract and store unique RF signal characteristics
Develop fingerprint matching and retrieval systems to identify previously observed signals
Implement monitoring and logging throughout the pipeline to ensure data quality and system reliability
Integrate transformer-based and other neural network models into production workflows
Optimize data preprocessing and feature extraction for ML model inputs
Implement efficient batching and inference strategies for real-time or near-real-time processing
Collaborate with ML researchers to transition models from development to production
Design database schemas for storing signal fingerprints and associated metadata
Implement efficient similarity search and matching algorithms for fingerprint comparison
Build APIs and interfaces for querying the fingerprint database
Manage data versioning and provenance throughout the workflow
Write clean, maintainable, and well-documented Python code
Develop comprehensive unit and integration tests for pipeline components
Use configuration management tools (e.g., Hydra) for flexible system parameterization
Implement CI/CD practices for continuous deployment and testing
Create visualization and reporting tools for pipeline performance metrics