Machine Learning Engineer
Core
Develop machine learning solutions to enhance performance in wireless communication systems and signal processing for mission-critical applications.
Role type
Machine Learning Engineer (Signal Processing & Wireless Systems)
Builds
Large-scale, high-throughput systems handling vast quantities of RF data for mobile ad-hoc networks and electronic warfare.
Domain
Defense, Law Enforcement, and Critical Infrastructure (Wireless Communications & Signal Intelligence)
Deliverable
production ML models
Required skills
Python, PyTorch or TensorFlow, RF signal processing, SDR, supervised and unsupervised learning, statistical modeling, linear algebra, probability
Preferred skills
Cloud infrastructure (Azure/AWS), containerization (Docker/Kubernetes), Linux/DevOps, relational/NoSQL databases, sovereign cloud environments
Technologies
PyTorch, TensorFlow, SDR, Azure, AWS, Docker, Kubernetes, Jira, Azure DevOps
Responsibilities
Manage inputs from unusual sources including SDR captures over wide RF signal ranges; Combine signal processing, probability, statistics, and AI to build high-throughput systems; Collaborate with UX and infrastructure engineers to integrate ML algorithms across edge compute to data centers; Stay current with ML research for wireless and embedded systems.
Seniority
Senior, hands-on IC
