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Embedded Machine Learning Engineer Jobs (NOW HIRING)

Velo3D

Machine Learning Engineer

Fremont, CA

$150K - $220K/yr

We are seeking a Machine Learning Engineer to join our team developing machine learning solutions ... Work with print software and embedded teams to integrate validated models into production code ...

Velo3D

Machine Learning Engineer

Fremont, CA · On-site

$150K - $220K/yr

We are seeking a Machine Learning Engineer to join our team developing machine learning solutions ... Work with print software and embedded teams to integrate validated models into production code ...

Velo3D

Machine Learning Engineer

Fremont, CA · On-site

$150K - $220K/yr

We are seeking a Machine Learning Engineer to join our team developing machine learning solutions ... Work with print software and embedded teams to integrate validated models into production code ...

Mixpeek

Machine Learning Engineer

Washington, DC · On-site

$180 - $240/hr

The Machine Forward Deployed Learning Engineer position requires a mix of software development, LLM ... Experience in a customer-facing or embedded delivery role. * Exposure to federated or privacy ...

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 ...

Paylocity

Machine Learning Engineer

Machine Learning Engineer Position Overview Paylocity is growing its Machine Learning Engineering organization! Our machine learning engineering team is responsible for developing infrastructure and ...

Paylocity

Machine Learning Engineer

Schaumburg, IL · On-site

Machine Learning Engineer Position Overview Paylocity is growing its Machine Learning Engineering organization! Our machine learning engineering team is responsible for developing infrastructure and ...

Motorola

Machine Learning Engineer

Los Angeles, CA

$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 ...

PassFort

Machine Learning Engineer

Berlin, MD · On-site

$79.93 - $137.02/hr

We are looking for a skilled Machine Learning Engineer with expertise in perception to strengthen ... Practical experience deploying deep learning models in real time on embedded hardware (TensorRT ...

sensmore

Machine Learning Engineer

Berlin, NH · On-site

$102.41 - $159.31/hr

We are looking for a skilled Machine Learning Engineer with expertise in perception to strengthen ... Practical experience deploying deep learning models in real time on embedded hardware (TensorRT ...

NTENT

Machine Learning Engineer

Carlsbad, CA · On-site

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...

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Embedded Machine Learning Engineer information

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$70K

$153.4K

$174K

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

As of Aug 21, 2026, the average yearly pay for embedded machine learning engineer in the United States is $153,383.00, according to ZipRecruiter salary data. Most workers in this role earn between $131,500.00 and $173,000.00 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.

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Embedded Machine Learning Engineer jobs near you
Infographic showing various Embedded Machine Learning Engineer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $153,383 per year, or $73.7 per hour.

Machine Learning Engineer

Velo3D

Fremont, CA

$150K - $220K/yr

Full-time

Medical, Retirement

Re-posted 19 days ago

Job description

Position Overview: 

We are seeking a Machine Learning Engineer to join our team developing machine learning solutions for quality assurance and process monitoring in additive manufacturing. Working closely with process engineers, software engineers, and fellow ML engineers, you will develop and deploy models using image, time-series, and machine log data from advanced manufacturing systems.

Prior experience in additive manufacturing or 3D printing is not required. We are particularly interested in candidates with scientific, engineering, or technical backgrounds who have applied machine learning to complex real-world problems involving sensor data, physical systems, or experimental datasets, and who enjoy working closely with domain experts to deliver practical, high-impact solutions.

Responsibilities

  • Develop ML models using in-process sensor data to identify anomalies and quality issues during printing. 

  • Build and iterate on training and evaluation workflows; document experiments and results for reproducibility. 

  • Own ML experimentation end to end: Design datasets, preprocessing pipelines, and training workflows; iterate on model architectures and metrics; document experiments and results for reproducibility. 

  • Help define data collection and management: Partner with process and software teams to improve how build data is ingested, cataloged, versioned, and made available for training and evaluation. 

  • Deploy models into production: Work with print software and embedded teams to integrate validated models into production code running on printer hardware, including performance and reliability considerations. 

  • Collaborate with supporting software engineers: Hand off validated Python prototypes for production hardening, provide clear specifications and acceptance criteria, and support integration and regression testing. 

Requirements

  • Bachelor's degree in Computer Science, Electrical Engineering, Applied Mathematics, or a related field; advanced degree preferred. 

  • 3+ years of experience building and evaluating machine learning models in a professional setting. 

  •  Hands-on experience with computer vision or image-based ML (e.g., segmentation, classification, or anomaly detection). 

  • Strong Python skills and experience with modern ML frameworks (e.g., PyTorch). 

  • Experience designing ML pipelines: data loading, preprocessing, training, evaluation, and experiment tracking. 

  • Comfort working in a production software environment: version control, code review, testing, and cross-functional collaboration. 

  • Ability to communicate technical tradeoffs clearly to engineers and non-engineers. 

  • Strong programming skills in Python or C++. 

  • Experience organizing and working with structured and unstructured datasets. 

  • Background in a STEM or scientific discipline, with demonstrated use of ML to address substantive technical or engineering problems. 

Bonus  

  • Experience with powder bed fusion or other additive manufacturing processes. 

  • Knowledge of manufacturing data workflows, IoT sensor data, or industrial automation systems. 

  • Experience with image-based or time-series machine learning. 

  • Familiarity with model deployment in production or embedded environments. 

  • Familiarity with cloud storage and data pipelines (e.g., AWS S3, batch retrieval workflows). 

  • Experience in domains such as robotics, aerospace, materials, instrumentation, scientific computing, or other fields where ML is applied to physical or experimental data. 

About the Company:
 
Velo, Velo3D, Sapphire and Intelligent Fusion are registered trademarks of Velo3D, Inc. Without Compromise, Flow, Flow Developer, and Assure are trademarks of Velo3D, Inc.
 
With the only SupportFree laser powder bed fusion capability, we enable on-demand manufacturing of production quality Titanium, Inconel, and Aluminum parts with an unprecedented degree of design freedom and quality control. The VELO3D award-winning solution includes an integrated offering of hardware and software: Sapphire metal AM production printer, Flow print preparation software, Assure quality assurance and control system, and an integrated manufacturing process that runs throughout the printing operation.
 
Our team enjoys excellent benefits including healthcare coverage and 401(K) employer contributions. We believe in transparency and recognizing exceptional efforts through our monthly all-hands meetings and team member appreciation awards.
 
Our job titles may span more than one career level. The starting base salary for this full-time position is between $150,000 and $220,000. This salary range reflects the minimum and maximum target for this position in the U.S. The actual base pay is dependent upon many factors, such as work experience, job-related skills, related education, work location, and market demands. The base pay range is subject to change and may be modified in the future. In addition to a competitive base salary and a comprehensive benefits package, this position may be eligible for other forms of compensation such as participation in a bonus and equity program, as applicable.
 
Velo3D provides equal employment opportunities to all employees and applicants for employment without regard to, and prohibits discrimination and harassment based on, race, color, religion, age, sex, national origin, disability, medical condition, genetic information, military or veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
 
This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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