1

Embedded Machine Learning Engineer Jobs (NOW HIRING)

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 ...

Job Summary We are seeking an experienced Machine Learning Engineer with strong hands-on expertise in building, training, deploying, monitoring, and maintaining production machine learning models.

Sr. Machine Learning Engineer Location: New York, NY Sponsorship: Yes Relocation: Yes Industry ... with machine learning in embedded applications: model quantization, fixed point neural networks ...

Machine Learning Engineer Location: Detroit, MI- Onsite Type: Full-time Security Clearance: No clearance required, must be clearable. The Machine Learning Engineer will be an essential member of the ...

Machine Learning Engineer Remote with occasional travel to Silver Spring, MD About @Orchard: @Orchard is a growing Woman-Owned Small Business and federal prime contractor delivering mission-critical ...

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled Machine Learning Engineer to join our core AI team. In this role, you will focus on deploying ...

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled Machine Learning Engineer to join our core AI team. In this role, you will focus on deploying ...

Machine Learning Engineer / Research Engineer Pay: $$110,000 - $165,000 Base Salary + Equity Shift: N/A Location: San Mateo, CA (Peninsula) - Onsite Preferred Schedule: Full time, Permanent Role Visa ...

Machine Learning Engineer

Manhattan, NY · On-site

$170.17 - $255.26/hr

Job Overview Machine Learning Engineer w/ Spotify USA Inc. in NY, NY. Bld productn systms that enrich & improve Spotify listeners' exp on Spotify usg machine learng techniques. Bach deg (U.S. or for ...

Showing results 41-60

Embedded Machine Learning Engineer information

See salary details

$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.

More about Embedded Machine Learning Engineer jobs

What cities are hiring for Embedded Machine Learning Engineer jobs?

Cities with the most Embedded Machine Learning Engineer job openings:

What states have the most Embedded Machine Learning Engineer jobs?

States with the most job openings for Embedded Machine Learning Engineer jobs include:

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.

Founding Machine Learning Engineer - Time-Series & Health AI | MyDentalWig

Mydentalwig

Lancaster, CA • On-site

$170 - $230/hr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 15 days ago


Job description

MYDENTALWIG
Advanced Manufacturing. AI-Driven Healthcare. Preventive Innovation.


Building the future of intelligent manufacturing systems across healthcare, semiconductors, and AI infrastructure.


Location: Lancaster, California (On-site)
Employment Type: Full-Time
Compensation: $170,000–$230,000 annually, depending on experience, plus equity participation through the Company’s Equity Incentive Plan (Option Pool).


About MYDENTALWIG

MYDENTALWIG is developing a new category of healthcare technology called Ingestion Intelligence™.


Our mission is to create the world’s first platform capable of detecting human ingestion behavior in real time and translating it into predictive metabolic intelligence using artificial intelligence, sensor technologies, and cloud computing.


By integrating hardware, machine learning, and metabolic science, we are building a platform designed to help people better understand how eating behaviors influence health before chronic disease develops.


As one of the Company’s earliest technical hires, you will help define the artificial intelligence architecture at the core of this platform.


About the Opportunity

We are seeking an exceptional Machine Learning Engineer with expertise in time-series analysis, predictive modeling, and applied artificial intelligence to lead development of the AI²™ Platform.


This is a founding engineering position responsible for designing, developing, and optimizing machine learning models capable of interpreting ingestion events, identifying behavioral patterns, and generating personalized metabolic predictions.


You will work closely with biomedical engineers, software developers, clinical advisors, and leadership to transform raw sensor data into meaningful, actionable intelligence.


This role offers the opportunity to solve complex scientific and engineering challenges while helping establish a new category of AI-enabled digital health technology.


Key Responsibilities

  • Design, develop, and deploy machine learning models for physiological and behavioral time-series data.

  • Develop algorithms capable of identifying ingestion events and modeling individualized metabolic responses.

  • Build predictive models that integrate data from DCI™, AI²™, Continuous Glucose Monitors (CGMs), and other health data sources.

  • Design scalable data pipelines for training, validation, and continuous model improvement.

  • Develop personalization algorithms using longitudinal behavioral and physiological data.

  • Collaborate with software engineers to integrate machine learning models into cloud and mobile environments.

  • Evaluate model performance using appropriate statistical and machine learning methodologies.

  • Contribute to scientific publications, invention disclosures, and patent development where appropriate.

  • Support future clinical validation studies through data analysis and model refinement.

  • Stay current with advances in artificial intelligence, machine learning, and digital health technologies.


Minimum Qualifications

  • Bachelor’s degree in Computer Science, Machine Learning, Artificial Intelligence, Biomedical Engineering, Data Science, or a closely related field.

  • Five or more years of professional experience developing machine learning models in production environments.

  • Strong experience with Python and machine learning frameworks such as PyTorch, TensorFlow, or similar platforms.

  • Solid understanding of supervised and unsupervised learning techniques.

  • Experience working with complex time-series datasets.

  • Strong analytical, mathematical, and statistical skills.

  • Excellent communication and collaboration abilities.


Preferred Qualifications

  • Master’s degree or Ph.D. in Machine Learning, Artificial Intelligence, Computer Science, Biomedical Engineering, or a related discipline.

  • Experience applying machine learning to healthcare, biomedical signals, wearable technologies, digital therapeutics, or medical devices.

  • Experience with physiological signal processing and multimodal sensor fusion.

  • Knowledge of cloud-based machine learning infrastructure and MLOps.

  • Familiarity with reinforcement learning, causal inference, or probabilistic modeling.

  • Experience with edge AI and embedded machine learning.

  • Publications in machine learning or biomedical AI.

  • Inventor on issued or pending patents.

  • Previous startup experience from concept through commercialization.

  • Competitive annual salary: $170,000–$230,000, based on qualifications and experience.

  • Stock option grant under the Company’s Equity Incentive Plan, subject to Board approval and the applicable Stock Option Agreement.

  • Equity awards are generally subject to a four-year vesting schedule with a one-year cliff.

  • Comprehensive medical, dental, and vision insurance (upon implementation of the Company’s benefits program).

  • 401(k) retirement plan (upon implementation of the Company’s retirement program).

  • Paid vacation, company holidays, and sick leave in accordance with Company policy and applicable California law.

  • Professional development opportunities, including conferences, technical training, and continuing education.

  • Opportunity to contribute to foundational intellectual property and help establish a new category of AI-enabled healthcare technology.


This is a founding engineering position. The successful candidate will help establish the Company’s artificial intelligence platform, influence key technical decisions, contribute to the Company’s intellectual property portfolio, and participate in building the engineering organization as MYDENTALWIG grows.


We are looking for individuals who are motivated not only by solving difficult technical problems, but also by the opportunity to build an enduring company with the potential for significant long‑term impact.


Why Join MYDENTALWIG?

Artificial intelligence is transforming healthcare, yet one of the most important behavioral variables—human ingestion—remains largely unmeasured.


At MYDENTALWIG, you will help build an AI platform designed to bridge that gap by combining sensing technology, machine learning, and metabolic science into an entirely new approach to preventive healthcare.


If you are passionate about developing intelligent systems that solve meaningful real-world problems, thrive in multidisciplinary environments, and want the opportunity to build foundational technology from the ground up, we encourage you to apply.

#J-18808-Ljbffr