Machine Learning Engineer

Motorola Solutions•Los Angeles, CA

5d•$120,000 - $160,000•Hybrid

About The Position

Would you like to join an incredibly talented group of people, doing very challenging work, with the prime directive of “Keeping Our Heroes Connected”? THE OPPORTUNITY Silvus is seeking a Machine Learning Engineer who will report to the R&D Director, Machine Learning on the R&D team. The successful individual in this role will focus on applying machine learning and data-driven techniques to improve the performance, efficiency, and adaptability of Silvus’ advanced MIMO radios and wireless networking systems. This individual will work closely with experts in wireless communications, DSP, networking, and embedded systems to develop ML-driven features that solve real-world problems in dynamic and challenging RF environments. This position is based at Silvus Technologies’ headquarters in the heart of vibrant West Los Angeles, CA, and is on a hybrid schedule. A minimum of 3 days onsite per week is expected. On-site days are Mondays, Wednesdays, and Thursdays. The following is a list of at least some of the current essential job functions of the position. Management may assign or reassign duties and responsibilities at any time at its discretion.

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.
Security Clearance: 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.
All employment is contingent upon the 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 of which the above are representative.