Machine Learning Engineer

Motorola Solutions•Los Angeles, CA

1d•Hybrid

About The Position

Silvus Technologies, a subsidiary of Motorola Solutions, is seeking a Machine Learning Engineer to join their R&D team. This role focuses on applying machine learning and data-driven techniques to enhance the performance, efficiency, and adaptability of Silvus’ advanced MIMO radios and wireless networking systems. The engineer will collaborate with experts in wireless communications, DSP, networking, and embedded systems to develop ML-driven features for challenging RF environments. This position is based in West Los Angeles, CA, with a hybrid schedule requiring a minimum of 3 days onsite per week (Mondays, Wednesdays, and Thursdays).

Requirements

M.S. or Ph.D. in Electrical Engineering, Computer Science, or a related field.
Minimum of 3 years of experience in machine learning, with demonstrated application to real-world problems; 1 year of machine learning experience with a PhD.
Strong foundation in supervised and unsupervised learning, signal processing, and statistical modeling.
Experience with Python ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn, etc.).
Familiarity with wireless communication concepts (e.g., PHY/MAC layers, MIMO, OFDM, spectrum access, SDRs).
Proficiency in MATLAB or C/C++ for signal processing algorithm development.
Active U.S. Government SECRET clearance or the ability to obtain one within 15 months of hire.
Must be a U.S. Citizen due to clients under U.S. government contracts.
Successful clearance of a background check and drug test.

Nice To Haves

Demonstrated experience with radio frequency signal classification, anomaly detection, or spectrum monitoring.
Familiarity with embedded machine learning, real-time systems, or deploying machine learning on edge devices.
Background in adaptive modulation, beamforming, or cognitive radio techniques.
Experience working with wireless standards such as 3GPP, IEEE 802.11/15, or military waveforms.
Experience with GPU acceleration or model optimization for constrained environments.
Excellent communication and collaboration skills.

Responsibilities

Research, design, and implement machine learning algorithms to enhance performance in wireless communication systems (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 Silvus’ radio firmware and networking stack.
Collaborate with cross-functional teams to define machine learning use cases and evaluate the impact of deployed models.
Contribute to the design of data pipelines and infrastructure for training, testing, and validating models.
Participate in performance benchmarking and iterative improvement cycles.
Stay current with the latest Machine Learning research for wireless and embedded systems.
Perform other related duties as assigned.