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Temporary Embedded Machine Learning Jobs in Whittier, CA

Motorola

Machine Learning Engineer

Los Angeles, CA

$150K - $180K/yr

Stay current with the latest machine learning research for wireless and embedded systems, applying ingenuity and a deep understanding of the problems at hand Required Skills * 4+ years experience as ...

Motorola

Machine Learning Engineer

Los Angeles, CA · On-site

$150K - $180K/yr

Stay current with the latest machine learning research for wireless and embedded systems, applying ingenuity and a deep understanding of the problems at hand Required Skills * 4+ years experience as ...

Masimo

Sr Engineer, AI/Machine Learning

Irvine, CA · On-site

$140K - $170K/yr

Implement physiological parameter measurement algorithms on embedded systems * Deliver high quality ... Algorithm development experience using machine learning techniques such as regression ...

Masimo

Sr Engineer, AI/Machine Learning

Irvine, CA · On-site

$140K - $170K/yr

Implement physiological parameter measurement algorithms on embedded systems * Deliver high quality ... Algorithm development experience using machine learning techniques such as regression ...

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Temporary Embedded Machine Learning information

See Whittier, CA salary details

$74K

$162.2K

$184K

How much do temporary embedded machine learning jobs pay per year?

As of Aug 29, 2026, the average yearly pay for temporary embedded machine learning in Whittier, CA is $162,165.00, according to ZipRecruiter salary data. Most workers in this role earn between $139,000.00 and $182,900.00 per year, depending on experience, location, and employer.

What is the difference between Temporary Embedded Machine Learning vs Embedded Software Engineer?

AspectTemporary Embedded Machine LearningEmbedded Software Engineer
CredentialsRelevant degrees in CS, EE, or data science; certifications in ML or embedded systemsDegrees in CS, EE; certifications in embedded systems or software development
Work EnvironmentProject-based, often in tech or manufacturing industries, with focus on ML integrationDesigning, developing, and testing embedded software in various industries like automotive, IoT
Industry UsageUsed in AI-driven embedded systems, IoT devices, and smart gadgetsUsed in consumer electronics, automotive, industrial automation

Temporary Embedded Machine Learning specialists focus on integrating machine learning models into embedded devices, often on a project basis. Embedded Software Engineers develop and maintain the software that runs directly on hardware. While both roles require embedded systems knowledge, the ML role emphasizes AI integration, whereas the embedded software engineer focuses on software development and system stability.

Temporary Embedded Machine Learning jobs near you

Machine Learning Engineer

Silvus Technologies

Los Angeles, CA

Full-time

Re-posted yesterday

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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