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Embedded Machine Learning Engineer Jobs (NOW HIRING)

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

As a Machine Learning Engineer on our core AI/ML team, you will design and build GenAI-powered ... shared AI platform and embedded across products- Design, build, and own end-to-end GenAI ...

Health insurance Machine Learning Engineer 100% Remote We are seeking a highly skilled Machine Learning Engineer to design, develop, deploy, and maintain scalable machine learning solutions that ...

The role of Machine Learning Engineer involves working in a dynamic research environment and ... Embedded Software development. • At least 3 years of work experience in a relevant field. • ...

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 ...

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

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

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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 Jun 19, 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 are the key skills and qualifications needed to thrive as an Embedded Machine Learning Engineer, and why are they important?

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 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 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 June 2026, with employment types broken down into 50% Internship, and 50% Full Time. Highlights an 100% In-person job distribution, with an average salary of $153,383 per year, or $73.7 per hour.
Machine Learning Engineer - Embedded Insights

Machine Learning Engineer - Embedded Insights

Plaid Inc

New York, NY • On-site

$211K - $272K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted yesterday


Job description

We believe that the way people interact with their finances will drastically improve in the next few years. We're dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid's network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam.
The Embedded Insights team supports Plaid's mission to build a world-class suite of intelligence products. We identify the best opportunities to use machine learning in Plaid products, prove out those opportunities, and collaborate with cross-functional partners to turn them into real world production systems.
As a Machine Learning Engineer on the Embedded Insights team, you will drive machine learning initiatives from concept to production, working across the full model development lifecycle. You will leverage Plaid's unique datasets to identify high-impact opportunities for machine learning, develop proofs of concept to validate new approaches, and build MVP solutions that demonstrate customer value. Partnering closely with product managers, engineers, and other cross-functional stakeholders, you will embed within product teams to translate successful prototypes into scalable, customer-facing products. As solutions gain traction, you will help expand their reach by optimizing models for new use cases, improving system scalability, and incorporating customer feedback gathered before and after launch. You will also be responsible for maintaining and enhancing existing machine learning systems through feature development, retraining strategies, and robust monitoring frameworks, including metrics, alerts, and dashboards that ensure model performance, reliability, and long-term health.
Responsibilities:
  • Opportunity to shape Plaid's future as a company where intelligence products are a core value proposition.
  • Dive into one of the most unique datasets available in the industry and shape the strategy to leverage its value.
  • Work across many different areas and learn deeply about the entire Plaid product suite
  • Build products that empower millions of people to achieve financial freedom and opportunity.
  • Work closely with customers to ensure products meet their needs and demonstrate true impact.
  • Join a high ownership team where the greenfield opportunity is extremely high.

Qualifications:
  • 5+ years of experience in machine learning, including deploying machine learning models into real-world, customer facing systems.
  • High agency and creativity; experience identifying, defining, and proposing high impact machine learning opportunities.
  • Ability to analyze large and complex financial datasets to derive insights.
  • Advanced degree or equivalent work experience in Statistics, Economics, Mathematics, Data Science, or a related field.
  • Proficiency in SQL, Python, and data visualization/analysis tool.
  • Ability to clearly communicate complex technical systems and decision making.

Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to Plaid!
Plaid is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at accommodations@plaid.com.
Please review our Candidate Privacy Notice here.
Additional compensation in the form(s) of equity and/or commission are dependent on the position offered. Plaid provides a comprehensive benefit plan, including medical, dental, vision, and 401(k). Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.