Machine Learning Engineer

Motorola Solutions seeks a Machine Learning Engineer to apply data-driven techniques to improve MIMO radios and wireless networking systems. You will research and implement ML algorithms for tasks like link adaptation and interference mitigation, analyze RF datasets, and integrate models into firmware. This hybrid role is based in West Los Angeles.

• Research, design, and implement machine learning algorithms to enhance wireless communication system performance (e.g., link adaptation, interference mitigation, anomaly detection, spectrum sensing).
• Analyze real-world radio frequency datasets to extract insights and develop predictive models.
• Develop software prototypes and integrate ML algorithms with radio firmware and networking stack.
• Collaborate with cross-functional teams to define ML use cases and evaluate model impact.
• Contribute to data pipeline and infrastructure for training, testing, and validating models.
• Participate in performance benchmarking and iterative improvement cycles.
• Stay current with latest Machine Learning research for wireless and embedded systems.

• M.S. or Ph.D. in Electrical Engineering, Computer Science, or related field.
• Minimum 3 years of machine learning experience (or 1 year with Ph.D.), with real-world applications.