Machine Learning Engineer
Core
Develop machine learning solutions to enhance performance in wireless communication systems and signal processing for mission-critical applications.
Role type
Senior Machine Learning Engineer (Signal Processing & Wireless Systems)
Builds
Large-scale, high-throughput systems handling vast quantities of RF signal data for mobile ad-hoc networks and unmanned systems.
Domain
Defense, Law Enforcement, and Critical Infrastructure (Wireless Communications & AI)
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
Advanced degree in quantitative field, Relational/NoSQL databases, Cloud infrastructure (Azure/AWS), Linux, DevOps, Docker, Kubernetes, Regulated environments (sovereign clouds)
Technologies
Python, PyTorch, TensorFlow, SDR, Azure, AWS, Docker, Kubernetes, Jira, Azure DevOps
Responsibilities
Manage inputs from unusual sources including SDR captures over wide range of RF signals; Combine signal processing, probability, statistics, and AI to build large-scale systems; Collaborate with UX and infrastructure engineers to develop prototypes and integrate ML algorithms; Stay current with latest ML research for wireless and embedded systems.
Seniority
Senior, hands-on IC