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Wireless Machine Learning Engineer Jobs (NOW HIRING)

Motorola

Machine Learning Engineer

Los Angeles, CA

THE OPPORTUNITY Silvus is seeking a Machine Learning Engineer who will report to the R&D Director ... This individual will work closely with experts in wireless communications, DSP, networking, and ...

Qualcomm

Machine Learning Engineer

San Diego, CA · On-site

As a Machine Learning Engineer, you will develop and implement machine learning techniques and ... Company : Qualcomm designs wireless technologies and semiconductors that power connectivity ...

Motorola

Machine Learning Engineer

Los Angeles, CA

THE OPPORTUNITY Silvus is seeking a Machine Learning Engineer who will report to the R&D Director ... This individual will work closely with experts in wireless communications, DSP, networking, and ...

HeyMilo AI

Machine Learning Engineer

Manhattan, NY

Machine Learning Engineer Company: HeyMilo AI Location: New York, NY, USA Contract Details: Full-time HeyMilo AI is a fast-growing startup based in New York City that specializes in developing ...

Forhyre

Machine Learning Engineer

New York, NY

We are looking for a Machine Learning Engineer to help us create artificial intelligence products. Machine Learning Engineer responsibilities include creating machine learning models and retraining ...

Full Scope

Machine Learning Engineer

Reston, VA

Machine Learning Engineer Location: Fort Meade, MD Required Clearance : TS/SCI w/ Full-Scope Poly Salary: Competitive We are seeking a highly skilled and motivated Machine Learning Engineer to join ...

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Wireless Machine Learning Engineer information

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How much do wireless machine learning engineer jobs pay per year?

As of Jun 2, 2026, the average yearly pay for wireless machine learning engineer in the United States is $129,511.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,000.00 and $134,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Wireless Machine Learning Engineer, and why are they important?

To thrive as a Wireless Machine Learning Engineer, you need a strong background in wireless communications, signal processing, and machine learning, typically supported by a degree in electrical engineering, computer science, or a related field. Expertise in frameworks like TensorFlow or PyTorch, familiarity with wireless simulation tools (e.g., MATLAB, NS-3), and experience with relevant programming languages such as Python or C++ are commonly required. Strong problem-solving abilities, collaboration, and effective communication are vital soft skills for bridging the gap between machine learning and wireless domain experts. These skills enable the development of innovative, data-driven solutions that enhance wireless network performance and reliability.

How does a Wireless Machine Learning Engineer typically collaborate with hardware and software teams during product development?

Wireless Machine Learning Engineers often work closely with both hardware and software engineering teams to ensure seamless integration of ML models into wireless communication systems. This collaboration involves translating algorithmic requirements into hardware-compatible solutions, optimizing model performance for embedded or edge devices, and troubleshooting integration issues as they arise. Regular cross-functional meetings and joint testing sessions are common, enabling engineers to align on system constraints, data collection strategies, and deployment timelines. Effective communication and a strong understanding of both wireless technologies and ML workflows are key to successful collaboration.

What is a Wireless Machine Learning Engineer?

A Wireless Machine Learning Engineer is a professional who combines expertise in wireless communication systems and machine learning techniques to improve network performance, optimize resource allocation, and enable intelligent automation in wireless networks. They design, develop, and implement machine learning algorithms that help wireless devices and networks adapt to changing environments, manage interference, and enhance data transmission. This role often requires strong knowledge of signal processing, wireless protocols, and programming skills in languages such as Python or MATLAB.

What engineer can make $500,000 a year?

A Wireless Machine Learning Engineer can earn $500,000 or more annually, especially with extensive experience, advanced skills in wireless communication and machine learning, and working in high-paying industries or senior roles. Achieving this level often requires specialized expertise, certifications, and leadership responsibilities.

What is the difference between Wireless Machine Learning Engineer vs Wireless Data Scientist?

AspectWireless Machine Learning EngineerWireless Data Scientist
Required CredentialsBachelor's or Master's in CS, EE, or related; experience with ML frameworksBachelor's or Master's in CS, Statistics, or related; strong data analysis skills
Work EnvironmentDevelops ML models for wireless systems, embedded devices, network optimizationAnalyzes wireless data, builds predictive models, interprets large datasets
Employer & Industry UsageTelecom, IoT, wireless device manufacturersTelecom, network providers, wireless technology firms

Wireless Machine Learning Engineers focus on developing ML models for wireless systems and devices, while Wireless Data Scientists analyze wireless data to extract insights. Both roles require similar educational backgrounds and often work within the telecom and IoT industries, but their core responsibilities differ in application and focus.

Infographic showing various Wireless Machine Learning Engineer job openings in the United States as of May 2026, with employment types broken down into 89% Full Time, 7% Part Time, 3% Contract, and 1% Nights. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $129,511 per year, or $62.3 per hour.
Machine Learning Engineer

Machine Learning Engineer

Silvus Technologies

Los Angeles, CA • On-site

Other

Posted 3 days ago

Job description

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 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.

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