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Embedded Machine Learning Jobs (NOW HIRING)

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 ...

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 ...

Staff Embedded ML Engineer, Edge AI

Boston, MA ยท On-site

$142K - $187K/yr

About the Role We are seeking a highly motivated and experienced Embedded Machine Learning Engineer to join our growing Edge AI team. As a key contributor, you will lead the on-device inference and ...

About the Role We are seeking a highly motivated and experienced Embedded Machine Learning Engineer to join our growing Edge AI team. As a key contributor, you will lead the on-device inference and ...

Staff Embedded ML Engineer, Edge AI

Boston, MA ยท On-site

$142K - $187K/yr

About the Role We are seeking a highly motivated and experienced Embedded Machine Learning Engineer to join our growing Edge AI team. As a key contributor, you will lead the on-device inference and ...

They are seeking a Director of Machine Learning to define the ML strategy, lead the computer vision ... embedded inference) โ€ข Familiarity with warehouse, logistics, or supply chain domain โ€ข ...

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Embedded Machine Learning information

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$70K

$153.4K

$174K

How much do embedded machine learning jobs pay per year?

As of Sep 14, 2026, the average yearly pay for embedded machine learning 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 is an embedded machine learning?

An Embedded Machine Learning job involves developing and optimizing machine learning models to run efficiently on resource-constrained devices like microcontrollers, edge devices, and IoT hardware. Professionals in this role work on model compression, low-power inference, and real-time processing, ensuring AI capabilities can function without relying on cloud computing. Responsibilities often include data preprocessing, feature extraction, model training, and deployment on embedded systems using frameworks like TensorFlow Lite or Edge Impulse.

What are the key skills and qualifications needed to thrive in embedded machine learning?

To thrive in Embedded Machine Learning, you should have expertise in machine learning algorithms, embedded systems programming (e.g., C/C++, Python), and a solid understanding of hardware-software integration, typically backed by a degree in computer engineering, electrical engineering, or a related field. Familiarity with edge AI tools (such as TensorFlow Lite, ONNX, or Edge Impulse), microcontrollers, and real-time operating systems is highly valued, alongside relevant certifications such as Embedded Systems or AI certificates. Strong problem-solving skills, effective communication, and the ability to work cross-functionally are crucial soft skills in this field. These qualifications and qualities are vital for creating efficient, reliable AI solutions that operate seamlessly within resource-constrained environments and interdisciplinary project teams.

What are some common challenges faced by professionals working in embedded machine learning roles?

Professionals in embedded machine learning roles often face the challenge of optimizing machine learning models to run efficiently on resource-constrained hardware, such as microcontrollers or edge devices with limited memory and processing power. Balancing model accuracy, inference speed, and energy consumption can require creative problem-solving and deep knowledge of both hardware and software. Additionally, collaboration with hardware engineers, data scientists, and software developers is key, as projects typically require cross-functional teamwork to meet performance and deployment goals. Staying current with rapidly evolving tools and best practices is also important in this dynamic field.

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Infographic showing various Embedded Machine Learning job openings in the United States as of September 2026, with employment types broken down into 50% Internship, and 50% Contract. Highlights an 100% In-person job distribution, with an average salary of $153,383 per year, or $73.7 per hour.

Machine Learning Engineer

Cincinnati, OH โ€ข On-site

Kforce Technology Staffing
IT Servicesย โ€ขย 1 - 5K employees

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 11 days ago


Job description

RESPONSIBILITIES:
Kforce has a client that is seeking a Machine Learning Engineer in Cincinnati, OH.
Summary:
The Machine Learning Engineer is responsible for developing, implementing and maintaining knowledge-based or artificial intelligence application systems. The individual should ensure that information is converted into a format that is digestible and easy for end users to access the information and utilize it optimally.
The project this position will support is working to build a product for Sales Enablement which utilizes artificial intelligence - Generative AI and Machine Learning models to enhance user experience. This role will focus on the Machine Learning models, development, and model risk management in a team setting. They will be part of an existing on full stack and AI engineers.
Responsibilities:
* Understand business problems, comprehend data, systems and existing solutions, harvest data from data pipelines and propose models for Sales Enablement
* Build an ML model that can be delivered in production setting with available and existing data set
* Expected to build and test the model in the application setting and meet all client specific SDLC requirements
* Collaborate with Model Risk Management for evaluation and evidence gathering
* Understand AI principles and will implement them as controls or integrate required solutions
REQUIREMENTS:
* Must have experience in developing and deploying Generative AI embedded applications in a production setting within regulatory/financial environment
* Should have bias for action; Lead by example; An automation first and ownership mindset
* Must be able to articulate and guide team on implementing responsible AI principles in solution
* Should be able to guide and lead the team in Model risk evaluation, submit questionnaires and remediate risks identified.
* Should be able to lay down a clear framework for ML Ops and Governance cycle of AI applications
* Python, Java, Prior experience with Machine Learning models and MRM in a production setting
* Understand and have prior experience of Generative AI development, validation and evaluation techniques is a plus
The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.
We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.
Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.
This job is not eligible for bonuses, incentives or commissions.
Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.
By clicking ?Apply Today? you agree to receive calls, AI-generated calls, text messages or emails from Kforce and its affiliates, and service providers. Note that if you choose to communicate with Kforce via text messaging the frequency may vary, and message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You will always have the right to cease communicating via text by using key words such as STOP.

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About Kforce

Sourced by ZipRecruiter

Kforce is a professional staffing services firm that is located in Tampa, Florida, US. Operational since 1962, it specializes in flexible and direct hire staffing in Technology and Finance & Accounting, engaging over 23,000 highly skilled professionals annually with more than 4,000 customers. Kforce operates within various industry sectors such as healthcare, financial services, communications, and government. Their mission is to have a meaningful impact on all the lives they serve, with a focus on integrity, respect, and trust.

Industry

It services and finance and insurance

Company size

1,001 - 5,000 Employees

Headquarters location

Tampa, FL, US