Company Overview

At Motorola Solutions, we believe that everything starts with our people. We’re a global close-knit community, united by the relentless pursuit to help keep people safer everywhere. We build and connect technologies to help protect people, property and places. Our solutions foster the collaboration that’s critical for safer communities, safer schools, safer hospitals, safer businesses, and ultimately, safer nations. Connect with a career that matters, and help us build a safer future.

Department Overview

Silvus Technologies, a leading provider of advanced MANET and MIMO communications systems, is reshaping mesh network technology for mission-critical applications – on the ground, in the air and at sea. Its battle-proven StreamCaster family of MANET radios and proprietary MN-MIMO waveform provides the vital communications link for defense, law enforcement and public safety agencies around the world, and in the toughest operational environments.

With deep roots in DARPA research, Silvus Technologies develops world-class advanced communications technologies that are reshaping the tactical communications landscape. From pure line-of-sight to extreme non-line-of-sight, Silvus radios form a self-healing, self-forming mesh network, enabling secure and reliable connectivity, including video and high-bandwidth data.

Silvus Technologies is a wholly owned subsidiary of Motorola Solutions, Inc.

Job Description

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.

ROLE AND 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.

REQUIRED QUALIFICATIONS

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.

PREFERRED KNOWLEDGE, SKILLS, AND ABILITIES

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.

WORKING CONDITIONS AND PHYSICAL REQUIREMENTS

Office environment.
Outdoor environment for demos.
Occasional exposure to heat, cold, and allergens while performing tests or demonstrations in the field.
While performing the duties of this job, the employee is required to do the following:

- Lift equipment up to 20 lbs. for the set-up of demonstrations and testing.

- Perform bending and reaching movements to place items on lower and higher shelves.

COMPENSATION: $120,000 - $160,000 / annually

The pay range is NOT a guarantee. It is based on market research and peer data and will vary depending on the candidate’s experience and qualifications.

NOTE - As a US Federal Contractor, Silvus Technologies requires that ALL candidates being considered for employment for any position (regardless of level) MUST be a U.S. Person (permanent resident or citizen). Stricter U.S. Citizen ONLY requirements (needed for some Engineering or R&D roles) will be included in the Required Qualifications section of the posted position. This does NOT apply to international positions; only job postings for positions located in the US.

All employment is contingent upon the successful clearance of a background check and drug test.

Basic 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.

Travel Requirements

Under 10%

Relocation Provided

Domestic

Position Type

Experienced

Referral Payment Plan

Yes

Our U.S. Benefits include:

Incentive Bonus Plans
Medical, Dental, Vision benefits
401K with Company Match
10 Paid Holidays
Generous Paid Time Off Packages
Employee Stock Purchase Plan
Paid Parental & Family Leave
and more!

EEO Statement

Motorola Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion or belief, sex, sexual orientation, gender identity, national origin, disability, veteran status or any other legally-protected characteristic.

We are proud of our people-first and community-focused culture, empowering every Motorolan to be their most authentic self and to do their best work to deliver on the promise of a safer world. If you’d like to join our team but feel that you don’t quite meet all of the preferred skills, we’d still love to hear why you think you’d be a great addition to our team.

We’re committed to providing an inclusive and accessible recruiting experience for candidates with disabilities, or other physical or mental health conditions. To request an accommodation, please complete this Reasonable Accommodations Form so we can assist you.