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This listing was closed on Jul 18, 2026.
Browse Open JobsSenior Machine Learning Engineer
Summary by AIEngineer.careers
Senior Machine Learning Engineer is a Machine Learning Engineer role (full-time). with Motorola Solutions. in LOS ANGELES, US. Compensation shown: $195K–$225K. Imported listing (source: linkedin.com). Apply on the employer's site (linkedin.com).
Imported listing (source: linkedin.com) · Apply on linkedin.com
LOS ANGELES · US
$195K–$225K
Full-time
SENIOR
The sections below reproduce the third-party job description for reference. AIEngineer.careers does not write or control this text.
Imported job description
Sourced from linkedin.com
Develop machine learning solutions for wireless communication systems at Motorola Solutions' subsidiary Silvus Technologies. Work on enhancing MANET radios with AI, collaborating with a team to integrate ML algorithms across edge and data center scales.
Responsibilities
- Manage inputs from software defined radio captures over a wide range of RF signals. Combine signal processing, probability, statistics, and ML to build large-scale, high-throughput systems. Collaborate with UX designers, infrastructure engineers, and research scientists to develop prototypes and integrate ML algorithms.
Requirements
- 6+ years experience as a machine learning engineer. Expert knowledge in Python and PyTorch or TensorFlow. Strong foundation in supervised/unsupervised learning and statistical modeling. Strong mathematics background in linear algebra and probability. Strong written and oral communication skills.
Nice to Have
- Advanced degree in electrical and computer engineering, physics, mathematics, or statistics. Familiarity with relational and NoSQL databases. Familiarity with RF signal processing and SDR for signals intelligence or electronic warfare. Familiarity with Azure and/or AWS. Experience with Jira, Azure DevOps, Linux, DevOps, Docker, Kubernetes. Familiarity with regulated environments.
Motorola Solutions
Chicago · US · 21000+ employees
Motorola Solutions, Inc. provides public safety and enterprise security technology. Its ecosystem includes video security, command center software, and mobile radio communications for protected services.
