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Embedded Machine Learning Engineer Jobs in Tennessee

Deloitte

AI Solutions Architect

Nashville, TN · On-site

$60.75 - $80.25/hr

Certifications in artificial intelligence, machine learning, or cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Microsoft ...

Deloitte

Senior AI Engineer - SFL Scientific

Nashville, TN

$100K - $138K/yr

Work You'll Do As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and ...

ADDSOURCE

AI ML Engineer

Franklin, TN · On-site

AI ML Engineer Experience: Minimum 10+ Years Location: Franklin, TN Hybrid We are looking for an AI ... Responsibilities Lead end to end delivery of AI and machine learning initiatives with ownership of ...

New

Elevance Health

Gen AI Engineer

Nashville, TN · Hybrid

Collaborate closely with the MLOps, product teams, business stakeholders, machine learning engineers, and software engineers for the deployment of machine learning models into production environments ...

Elevance Health

Gen AI Engineer

Nashville, TN · Hybrid

Collaborate closely with the MLOps, product teams, business stakeholders, machine learning engineers, and software engineers for the deployment of machine learning models into production environments ...

DPR Construction

MLOps Engineer

Nashville, TN · On-site

We are looking for aMLOps Engineerto join our team and contribute to developing robust data solutionsto support our Machine Learning,Data Science, Data Engineering and Software Engineering. Position ...

Crowe LLP

Senior AI Engineer

Nashville, TN · On-site +1

$100K - $138K/yr

... innovation, embedded AI capabilities, and global delivery resources-all in service of solving ... The Senior AI Engineer 1 (Senior Staff) leads the development of advanced AI and machine learning ...

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All JobsEmbedded Machine Learning Engineer JobsEmbedded Machine Learning Engineer Jobs in Tennessee

Embedded Machine Learning Engineer information

See Tennessee salary details

$63.5K

$139.2K

$157.9K

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

As of Jul 8, 2026, the average yearly pay for embedded machine learning engineer in Tennessee is $139,213.00, according to ZipRecruiter salary data. Most workers in this role earn between $119,400.00 and $157,000.00 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.

What are popular job titles related to Embedded Machine Learning Engineer jobs in Tennessee? For Embedded Machine Learning Engineer jobs in Tennessee, the most frequently searched job titles are:
What job categories do people searching Embedded Machine Learning Engineer jobs in Tennessee look for? The top searched job categories for Embedded Machine Learning Engineer jobs in Tennessee are:
What cities in Tennessee are hiring for Embedded Machine Learning Engineer jobs? Cities in Tennessee with the most Embedded Machine Learning Engineer job openings:
Embedded Machine Learning Engineer jobs near you
Software Engineer- Embedded/Firmware

Software Engineer- Embedded/Firmware

Oak Ridge Associated Universities

Knoxville, TN • On-site

$98K - $134K/yr

Other

Retirement

Re-posted 14 days ago

Job description

Software Engineer- Embedded/Firmware
Job Locations US-TN-Knoxville, TN
ID 2026-2744
Category Science & Engineering
Type Full Time
Overview

ORAU is conducting the search on behalf of Type One Energy for a permanent, fulltime Software Engineer (Embedded/Firmware) in Knoxville, Tennessee.

Location: Knoxville TN

Salary: Highly Competitive Plus Benefits

Role: Permanent, full time

Reporting to: Director of Electrical and Software Engineering

About Type One Energy

Type One Energy Group is mission-driven to provide sustainable, affordable fusion power to the world. Established in 2019 and venture-backed in 2023, the company is led by a team of globally recognized fusion scientists with a strong track record of building state-of-the-art stellarator fusion machines, together with veteran business leaders experienced in scaling companies and commercializing energy technologies.

If you are searching for the best new ideas and share our vision, join us as a "Software Engineer- Embedded/Firmware".

Type One Energy offers:

In addition to a basic salary and yearly bonus, you will also get...

    Stock and share options
  • Relocation allowance
  • Insurance plans
  • 401k retirement options
  • And many more great voluntary benefits

Type One Energy applies proven advanced manufacturing methods, modern computational physics and high-field superconducting magnets to develop its optimized stellarator fusion energy system. Its FusionDirect development program pursues the lowest-risk, shortest-schedule path to a fusion power plant over the coming decade, using a partner-intensive and capital-efficient strategy.

Type One Energy is committed to community engagement in the development and deployment of its clean energy technology. For more information, visit www.typeoneenergy.com or follow us on LinkedIn.

Responsibilities

Your role in the mission:

The Software Engineer - Embedded / Firmware will design and develop low-level software and firmware for instrumentation and control (I&C) systems supporting stellarator devices and associated equipment. This role focuses on embedded platforms, FPGA-based systems, real-time operating environments, and hardware integration.

The successful candidate will work closely with electrical, controls, and systems engineers to enable reliable operation of safety-critical and high-performance hardware. You will:

  • Develop low-level embedded software and firmware, including I&C device drivers
  • Design and implement FPGA control software using hardware description languages
  • Develop, customize, and maintain embedded operating systems such as real-time Linux and PetaLinux
  • Support printed circuit board assembly (PCBA) development in collaboration with hardware teams
  • Perform hardware bring-up, validation, and debugging of new embedded platforms
  • Implement and maintain software build systems, testing, and CI/CD pipelines
  • Integrate firmware with higher-level control systems and applications
  • Troubleshoot complex hardware-software interactions
  • Create technical documentation including design specifications, interface definitions, and test procedures
  • Participate in system integration, verification, and commissioning activities
Qualifications

What you'll need:

  • Bachelor's or Master's degree in Computer Engineering, Electrical Engineering, Software Engineering, or a related field
  • Minimum 3 years of experience in embedded software or firmware development
  • Strong experience with PetaLinux and real-time Linux environments
  • FPGA development experience using VHDL and/or Verilog
  • Experience with standard embedded peripherals and communication protocols, including:
    • ADC, DAC
    • IC, SPI
    • Ethernet / TCP/IP
    • Serial interfaces and low-level hardware communication
  • Experience with version control and CI/CD tools (e.g., Jenkins, GitHub Actions)
  • Strong debugging and problem-solving skills across hardware and software domains
  • Ability to work effectively in a multidisciplinary engineering environment

Preferred Qualifications

  • Experience with industrial automation or control systems
  • Familiarity with LabVIEW and National Instruments hardware platforms
  • Experience working in regulated industries such as medical devices, automotive, aerospace, nuclear, or energy
  • Knowledge of safety-critical or high-reliability embedded systems
  • Experience with system-level integration and testing of complex equipment
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