Machine Learning Engineer

Medium; California (MO); Hybrid; USD 100,000 - 140,000; Full time

Job summary

Silvus Technologies, a Motorola Solutions subsidiary, is seeking a Machine Learning Engineer to apply ML to improve the performance of its MIMO radios and wireless networks. Based in West Los Angeles, CA, this hybrid role requires at least 3 onsite days weekly.

You will collaborate with experts in wireless communications, DSP, and embedded systems to develop ML-driven features and help design data pipelines and firmware integrations.

Qualifications

• BS in Electrical Engineering, Computer Science, or related field with 2+ years in ML or advanced degree acceptable.
• Strong foundation in supervised and unsupervised learning and statistical modeling.
• Experience with Python ML frameworks (TensorFlow, PyTorch, scikit-learn).
• Exposure to MATLAB or C/C++ for signal processing algorithm development.
• Must be a U.S. Citizen due to government contracts.
• Background check and drug test clearance required.

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 RF 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 ML use cases and evaluate the impact of deployed models.
• Contribute to data pipelines and infrastructure for training, testing, and validating models.
• Stay current with the latest Machine Learning research for wireless and embedded systems.
• Perform other related duties as needed.

Skills

Python ML frameworks

ML fundamentals

Data analysis

RF signal processing

Education

Bachelor of Science in Electrical Engineering, Computer Science, or related field

MS/PhD preferred in EE/CS or related field

Tools

MATLAB

C/C++

Job description

Machine Learning Engineer

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.

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

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.

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 RF 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 ML 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

• Bachelor of Science degree in Electrical Engineering, Computer Science, Computer Engineering, or related field plus a minimum of 2 years of experience in machine learning, with demonstrated application to real‑world problems; no experience required with an advance degree (MS or PhD)
• Strong foundation in supervised and unsupervised learning and statistical modeling.
• Experience with Python ML frameworks (e.g., TensorFlow, PyTorch, scikit‑learn, etc.).
• Exposure to MATLAB or C/C++ for signal processing algorithm development.
• 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

• MS. or Ph.D. in Electrical Engineering, Computer Science, or a related field.
• Demonstrated experience with RF signal classification, anomaly detection, or spectrum monitoring.
• Proficiency in MATLAB or C/C++ for signal processing algorithm development.
• Familiarity with wireless communication concepts (e.g., PHY/MAC layers, MIMO, OFDM, spectrum access).
• Familiarity with embedded ML, real‑time systems, or deploying ML 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

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.

CA Pay Range: $100,000-$140,000 USD

Consistent with Motorola Solutions values and applicable law, we provide the following information to promote pay transparency and equity. Pay within this range varies and depends on job‑related knowledge, skills, and experience. The actual offer will be based on the individual candidate.

Important Eligibility and Compliance

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.

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.