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Embedded Machine Learning Engineer Jobs in Friendship, TN

Assa Abloy

Tool & Die Tech

Milan, TN · On-site

Work with supervision and engineering in the planning and installation of new machinery and ... Tuition Reimbursement, Learning and Career Development opportunities * Flexible Spending * Employee ...

ASSA ABLOY

Tool & Die Tech

Milan, TN

Work with supervision and engineering in the planning and installation of new machinery and ... Tuition Reimbursement, Learning and Career Development opportunities * Flexible Spending * Employee ...

Domtar

Maintenance Technichian

Brownsville, TN

... learning and growth. The location in Brownsville, (Tennessee, United States), is seeking talent to ... Mechanical ability including troubleshooting abilities on paper converting machines * Use ...

Hitachi

IT Service Delivery Manager

Alamo, TN · On-site

Enable secure machine and network connectivity Your background * Bachelor's degree in Computer ... Microsoft DevOps and Microsoft Azure * SAP S/4HANA * Information, Data & Analytics, and Business ...

Hitachi, Ltd.

IT Service Delivery Manager

Alamo, TN · On-site

Enable secure machine and network connectivity Your background * Bachelor's degree in Computer ... Microsoft DevOps and Microsoft Azure * SAP S/4HANA * Information, Data & Analytics, and Business ...

Prysmian

Maintenance Technician

Jackson, TN · On-site

$26.50 - $28.50/hr

Candidate must be capable of independent decision making and providing leadership to those learning ... machine issues. * Must be able to climb a 15' ladder. * Must be able to lift or pull a minimum of ...

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All JobsEmbedded Machine Learning Engineer JobsEmbedded Machine Learning Engineer Jobs in Friendship, TN

Embedded Machine Learning Engineer information

See Friendship, TN salary details

$59.7K

$130.8K

$148.3K

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

As of Jul 15, 2026, the average yearly pay for embedded machine learning engineer in Friendship, TN is $130,761.00, according to ZipRecruiter salary data. Most workers in this role earn between $112,100.00 and $147,500.00 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.

What cities near Friendship, TN are hiring for Embedded Machine Learning Engineer jobs? Cities near Friendship, TN with the most Embedded Machine Learning Engineer job openings:
Embedded Machine Learning Engineer jobs near you
Data Scientist-Direct Hire-6-Month Register

Data Scientist-Direct Hire-6-Month Register

US Department of the Treasury

Jackson, TN • On-site

$125K/yr

Other

Posted 14 days ago

U.S. Department Of The Treasury rating

8.2

Company rating: 8.2 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

237th of 693 rated public administrative organizations

Job description

WHAT IS DATA AND ANALYTICS (DA)-RESEARCH APPLIED ANALYTICS & STATISTICS (RAAS)?

A description of the business units can be found at: https://www.jobs.irs.gov/about/who/business-divisions

  • Position(s) are to be filled in the following area(s):
    • DAO DATA AND ANALYTICS
  • Consider each location carefully when applying. If you are selected for a location, that location will become your official post of duty.
REVIEW THE ADDITIONAL INFORMATION BELOW FOR FURTHER DETAILSQualifications:Federal experience is not required. Experience may have been gained in the public sector, private sector or through Volunteer Service. One year of experience refers to full-time work; part-timework is considered on a prorated basis. To ensure full credit for your work experience, please indicate dates of employment by month/day/year, and indicate number of hours worked per week, on your resume.
You must meet the following requirements by the cut-off dates as shown in announcement under the 'How to Apply' section.
QUALIFICATION REQUIRMENTS: BASIC REQUIREMENTS All GRADES: EDUCATION:
You must have a bachelor's or higher degree in mathematics, statistics, computer science, data science or other field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
OR
COMBINATION OF EDUCATION AND EXPERIENCE: A combination of education and experience that includes courses equivalent to a major field of study (30 semester hours) as shown in the paragraph above, plus additional education or appropriate experience.
AND
SPECIALIZED EXPERIENCE GRADE 14: In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-13 grade level in the Federal service. Specialized experience for this position includes experience performing all the following:
  • Leading data science or statistical analysis initiatives by defining project scope, analytic approach, data requirements, schedules, deliverables, or success measures; coordinating work across data, program, business, or technology stakeholders; and developing findings or recommendations for program or operational decisions.
  • Developing or applying statistical, machine learning, operations research, artificial intelligence, or other data science methods to evaluate programs, operations, compliance, or organizational performance, for example forecasting, predictive or prescriptive modeling, optimization, natural language processing or text analytics, graph or link analysis, neural networks or deep learning, or exploratory data analysis.
  • Overseeing data preparation, data quality, data governance, data certification, or analytic product delivery using programming, query, scripting, or analytic tools, such as Structured Query Language (SQL), R, Python, SAS, or equivalent tools, to support reproducible analysis, reporting, modeling, or decision-support products.
  • Experience manipulating datasets in relational databases (e.g., Compliance Data Warehouse, Enterprise Data Platform).
  • Advising managers or senior leaders on data science findings, automation opportunities, policy or program impacts, resource implications, risks, or recommended changes to processes, procedures, or operations.
  • Providing technical guidance, review, or mentoring to analysts or data scientists and preparing technical reports, briefings, presentations, or documentation that explain methods, assumptions, limitations, validation results, success measures, key performance indicators, or recommendations.
AND
You must also meet the following requirements:
  • MINIMUM AGE REQUIREMENT: Minimum age for federal employment is 18 years old, or at least 16 years old and have:
    • Graduated from high school or been awarded a certificate equivalent to graduating from high school; or
    • Completed a formal vocational training program; or
    • Received a statement from school authorities agreeing with your preference for employment rather than continuing your education
For more information on qualifications please refer to OPM's Qualifications Standards.Education:A college or university degree generally must be from an accredited (or pre-accredited) college or university recognized by the U.S. Department of Education. For a list of schools which meet these criteria, please refer to Department of Education Accreditation page.
FOREIGN EDUCATION: Education completed in foreign colleges or universities may be used to meet the requirements. You must show proof the education credentials have been deemed to be at least equivalent to that gained in conventional U.S. education program. It is your responsibility to provide such evidence when applying. Click here (Section 3, Explanation of Terms) or here for Foreign Education Credentialing instructions.
We recommend choosing an evaluator from a member organization of one of the following national associations of credential evaluation services: National Association of Credential Evaluation Services (NACES) or Association of International Credentials Evaluators (AICE).Employment Type: OTHER

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