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Embedded Machine Learning Engineer Jobs in Pasadena, CA

Machine Learning Engineer

Los Angeles, CA ยท On-site

$150K - $180K/yr

Stay current with the latest machine learning research for wireless and embedded systems, applying ... Experience with Linux, DevOps (command line) * Experience with containerized infrastructure (Docker ...

The Role We are seeking a Machine Learning Engineer to develop advanced models for extracting ... Exposure to embedded or edge deployment constraints * Background in applied domains involving ...

Machine Learning Engineer

Los Angeles, CA ยท On-site

$150 - $180/hr

Stay current with the latest machine learning research for wireless and embedded systems, applying ... Experience with Linux, DevOps (command line) * Experience with containerized infrastructure (Docker ...

As a Senior Machine Learning Engineer, you will design, build, and scale advanced software systems that automate Design for Manufacturing analysis, leveraging deep learning and computer vision ...

Machine Learning Engineer

Los Angeles, CA ยท On-site

$180 - $250/hr

Role Description Founding Data Scientist / Machine Learning Engineer We're looking for a highly ambitious Data Scientist to help build the predictive intelligence layer behind nowfluence. This is not ...

Machine Learning Engineer

Torrance, CA ยท On-site

$160K - $300K/yr

As a Senior Machine Learning Engineer, you will play a key role in designing, building, and scaling these systems end to end. What You'll Do: * Research, develop and deploy cutting-edge deep learning ...

Machine Learning Engineer, Integrity Applied AI Engineering - San Francisco Apply now (opens in a new window) About the Team The Integrity team at OpenAI is dedicated to ensuring that our cutting ...

We are seeking a Staff Machine Learning Engineer / Data Scientist to serve as a technical anchor for our machine learning and AI capabilities. Reporting directly to the Director of Recommendation ...

New

Machine Learning Engineer II

Los Angeles, CA ยท On-site

$105K - $143K/yr

In this role you will work with a high performing team of applied scientists, machine learning engineers, and software development engineers that has delivered a number of AI/ML systems to production ...

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Embedded Machine Learning Engineer information

See Pasadena, CA salary details

$76.4K

$167.3K

$189.8K

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

As of Sep 6, 2026, the average yearly pay for embedded machine learning engineer in Pasadena, CA is $167,311.00, according to ZipRecruiter salary data. Most workers in this role earn between $143,400.00 and $188,700.00 per year, depending on experience, location, and employer.

What does an embedded machine learning engineer do?

An Embedded Machine Learning Engineer designs and implements machine learning models that can run efficiently on embedded systems, such as microcontrollers and edge devices. Their work involves optimizing algorithms to fit within the resource constraints of these devices, integrating ML models into hardware, and ensuring real-time performance. They collaborate closely with hardware engineers and software developers to deploy intelligent features in products like smart sensors, IoT devices, and autonomous systems.

What are the key skills and qualifications needed to thrive as an embedded machine learning engineer?

To thrive as an Embedded Machine Learning Engineer, you need expertise in machine learning algorithms, embedded systems programming (C/C++ or Python), and a solid understanding of hardware constraints, usually supported by a degree in computer science, electrical engineering, or related fields. Familiarity with tools like TensorFlow Lite, ONNX, microcontroller SDKs, and experience with real-time operating systems (RTOS) are typically required. Strong problem-solving, communication skills, and the ability to collaborate across multidisciplinary teams help you stand out in this role. These skills are crucial for efficiently deploying intelligent models on resource-constrained devices, ensuring optimal performance and seamless integration in real-world applications.

What are some common challenges faced by embedded machine learning engineers when deploying models to hardware devices?

One of the main challenges for Embedded Machine Learning Engineers is optimizing machine learning models to run efficiently on devices with limited memory, processing power, and energy capacity. Ensuring real-time performance while maintaining accuracy often requires model quantization, pruning, or using lightweight architectures. Additionally, engineers must carefully manage hardware-software integration and address issues like compatibility with various microcontrollers and ensuring secure, reliable updates for deployed models. Close collaboration with hardware engineers and software developers is essential to overcome these challenges and deliver robust embedded AI solutions.

What is the difference between Embedded Machine Learning Engineer vs Firmware Engineer?

AspectEmbedded Machine Learning EngineerFirmware Engineer
Required CredentialsBachelor's/Master's in Computer Science, Electrical Engineering, or related; knowledge of ML frameworksBachelor's in Electrical Engineering, Computer Engineering, or related; embedded systems experience
Work EnvironmentDevelops ML models for embedded devices, often in IoT or smart devicesDesigns and implements low-level firmware for hardware devices
Industry UsageTech companies, IoT, consumer electronics, automotiveConsumer electronics, automotive, industrial equipment

The Embedded Machine Learning Engineer focuses on integrating machine learning models into embedded systems, while the Firmware Engineer specializes in developing low-level software for hardware devices. Both roles require embedded systems knowledge but differ in their core focus and skill sets.

What are popular job titles related to Embedded Machine Learning Engineer jobs in Pasadena, CA?

For Embedded Machine Learning Engineer jobs in Pasadena, CA, the most frequently searched job titles are:

What job categories do people searching Embedded Machine Learning Engineer jobs in Pasadena, CA look for?

The top searched job categories for Embedded Machine Learning Engineer jobs in Pasadena, CA are:

What cities near Pasadena, CA are hiring for Embedded Machine Learning Engineer jobs?

Cities near Pasadena, CA with the most Embedded Machine Learning Engineer job openings:

Infographic showing various Embedded Machine Learning Engineer job openings in Pasadena, CA as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 22% Part Time, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $167,311 per year, or $80.4 per hour.

Machine Learning Engineer

Silvus Technologies

Los Angeles, CA โ€ข On-site

Full-time

Re-posted 8 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.ย  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.ย  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.ย  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.

ย 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.

ย 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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