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Embedded Machine Learning Engineer Jobs in Dayton, OH

Lead Signal Processing Researcher

Dayton, OH ยท On-site

$173K - $216K/yr

... algorithms, machine learning algorithms, systems analysis, and real-time embedded processor ... PhD, MS, or BS in Electrical Engineering, Applied Mathematics, Physics, or related technical ...

... algorithms, machine learning algorithms, systems analysis, and real-time embedded processor ... PhD, MS, or BS in Electrical Engineering, Applied Mathematics, Physics, or related technical ...

Lead Signal Processing Researcher

Dayton, OH ยท On-site

$173K - $216K/yr

... algorithms, machine learning algorithms, systems analysis, and real-time embedded processor ... PhD, MS, or BS in Electrical Engineering, Applied Mathematics, Physics, or related technical ...

... algorithms, machine learning algorithms, systems analysis, and real-time embedded processor ... PhD, MS, or BS in Electrical Engineering, Applied Mathematics, Physics, or related technical ...

... algorithms, machine learning algorithms, systems analysis, and real-time embedded processor ... PhD, MS, or BS in Electrical Engineering, Applied Mathematics, Physics, or related technical ...

Showing results 41-60

Embedded Machine Learning Engineer information

See Dayton, OH salary details

$68K

$149.1K

$169.1K

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

As of Aug 19, 2026, the average yearly pay for embedded machine learning engineer in Dayton, OH is $149,083.00, according to ZipRecruiter salary data. Most workers in this role earn between $127,800.00 and $168,100.00 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.

What are popular job titles related to Embedded Machine Learning Engineer jobs in Dayton, OH?

For Embedded Machine Learning Engineer jobs in Dayton, OH, the most frequently searched job titles are:

What job categories do people searching Embedded Machine Learning Engineer jobs in Dayton, OH look for?

The top searched job categories for Embedded Machine Learning Engineer jobs in Dayton, OH are:

What cities near Dayton, OH are hiring for Embedded Machine Learning Engineer jobs?

Cities near Dayton, OH with the most Embedded Machine Learning Engineer job openings:

Infographic showing various Embedded Machine Learning Engineer job openings in Dayton, OH as of August 2026, with employment types broken down into 1% As Needed, 71% Full Time, 25% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $149,083 per year, or $71.7 per hour.

Lead Signal Processing Researcher

STR

Dayton, OH โ€ข On-site

$173K - $216K/yr

Full-time

Re-posted yesterday


Job description

About the Team:

The Sensors Division at STR focuses on technology development for advanced sensor systems and platforms in support of national security requirements. Our particular focus areas include airborne/spaceborne/surface-based radar, electronic warfare, underwater acoustics, hyperspectral imaging, and EO/IR sensing. To support these missions, the Division's efforts span multiple technical areas, including RF analog/digital hardware, acoustic hardware, signal processing algorithms, machine learning algorithms, systems analysis, and real-time embedded processor implementation.

The Algorithms, Processing and Experimentation (APEX) Group specializes in development of RF/radar modes, skills and applications, with particular emphasis on advanced signal processing chains and associated algorithm research. We mature these technologies with the objective of implementation, integration, and eventual utility in RF-based systems, typically tailoring our work for highly specific Defense (e.g., Air Force, Space Force, Navy, DARPA, etc.) and Intelligence Community needs.

About the Role:

As a Lead Signal Processing Researcher, you will create and lead technical teams that develop, test, integrate, and demonstrate novel signal processing, optimization, and machine learning algorithms for advanced electronic warfare and sensor applications.

A successful candidate will have demonstrated leadership skills and substantial expertise in several of the following areas: optimization, electronic warfare, adaptive signal processing, machine learning, algorithm development, algorithm integration, test & evaluation, model & simulation, systems engineering, radar systems, or communications systems. This position requires skills working as part of and leading multi-disciplinary teams designing, analyzing, integrating, and demonstrating signal processing algorithms for complex systems.

What you will do:

  • Develop electronic warfare and radar system concepts, signal processing and machine learning algorithms, and RF solutions to remote sensing challenges
  • Provide technical leadership to small, multi-disciplinary teams that develop, implement, test, and integrate novel sensing, electronic warfare, and signal processing systems
  • Direct Modeling and Simulation activities of advanced RF systems in support of algorithm development, test, and integration
  • Plan and support algorithm test and evaluation activities, including performance assessment in laboratory and field environments
  • Clearly communicate with customers, stakeholders, sponsors, prime- and subcontractors

Who you are:

  • Active Security Clearance, with eligibility to support special access programs, for which US Citizenship is required by the US government
  • PhD, MS, or BS in Electrical Engineering, Applied Mathematics, Physics, or related technical discipline with 3-8+ years of relevant experience depending on degree
  • Strong scientific programming skills including Matlab, Python, Simulink and/or C/C++
  • Strong communication skills and the ability to describe complex technical concepts to fellow researchers as well as to non-technical people
  • Ability to translate customer requirements to determine research focus
  • Ability to create and present deep technical briefings as well as high-level briefings to Customers and senior management
  • Experience with designing, implementing, testing, and analyzing ML/AI algorithms
  • Strong understanding of radar architectures, waveforms, modes, and RF signal chains

Even Better:

  • Current TS/SSBI with SCI and ability to gain and hold SCI/SAP accreditations
  • Experience with advanced RF system concepts, signal processing, open architectures, and systems integration
  • Experience in Software Development
  • Ability to survey literature to determine state-of-the-art, incorporate recent research, and transition it into integrated, tested solutions
  • Understanding and experience interacting with decision-makers and customers to translate mission needs into an end-to-end, integrated analytical solution

Pay Information
Full-Time Salary Range: $173,000 - $216,000

The salary range listed is based on external market data. Offers are based on factors, such as but not limited to, the candidate's experience, education, training, key skills/critical skills, security clearances, and prevailing market and business conditions.