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Embedded Machine Learning Jobs in Dallas, TX (NOW HIRING)

E-Space

Embedded Software Engineering Intern

Arlington, TX

$118K - $155K/yr

Help collect and validate sensor datasets that feed on-device machine learning models, and assist ... Embedded debugging rewards people who keep pulling the thread. * Ability to work on-site in ...

E-Space

Embedded Software Engineering Intern

Arlington, TX · On-site

$118K - $155K/yr

Help collect and validate sensor datasets that feed on-device machine learning models, and assist ... Embedded debugging rewards people who keep pulling the thread. * Ability to work on-site in ...

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Embedded Machine Learning information

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$69.2K

$151.7K

$172.1K

How much do embedded machine learning jobs pay per year?

As of Aug 25, 2026, the average yearly pay for embedded machine learning in Dallas, TX is $151,732.00, according to ZipRecruiter salary data. Most workers in this role earn between $130,100.00 and $171,100.00 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.

What are popular job titles related to Embedded Machine Learning jobs in Dallas, TX?

For Embedded Machine Learning jobs in Dallas, TX, the most frequently searched job titles are:

What job categories do people searching Embedded Machine Learning jobs in Dallas, TX look for?

The top searched job categories for Embedded Machine Learning jobs in Dallas, TX are:

Embedded Machine Learning jobs near you
Infographic showing various Embedded Machine Learning job openings in Dallas, TX as of August 2026, with employment types broken down into 21% Internship, and 79% Full Time. Highlights an 100% In-person job distribution, with an average salary of $151,732 per year, or $72.9 per hour.

Embedded Software Engineering Intern

Arlington, TX

E-Space
See more jobs at E-Spaceexternal

$118K - $155K/yr

Part-time

Medical, PTO

Posted 5 days ago

Job description

Ready to make connectivity from space universally accessible, secure and actionable? Then you've come to the right place!

E-Space is bridging Earth and space to enable hyper-scaled deployments of Internet of Things (IoT) solutions and services. We are building a highly-advanced low Earth orbit (LEO) space system that will fundamentally change the design, economics, manufacturing and service delivery associated with traditional satellite and terrestrial IoT systems.

We're intentional, we're unapologetically curious and we're 100% committed to innovate space-based communications and deliver actionable intelligence that will expand global economies, protect space and our planet and enhance our overall quality of life.

About the Role

We are looking for an Embedded Software Engineering Intern to work on real firmware for real hardware that ships. You will be embedded (pun intended) with a senior firmware engineer working on a sensor-rich, wireless-connected IoT device: writing production C on Zephyr RTOS, bringing up sensors, debugging on live boards at the bench, and moving data from the edge to the cloud. 

This is not a shadow-and-observe internship. You will have your own board, your own debugger, and your own work items from week one. You will pair daily with your mentor - at the whiteboard, at the bench, and in code review - and by the end of the internship you will have shipped at least one feature end-to-end on live hardware. 

What you will do:

Hands-on Development 

  • Write and debug firmware in C on Zephyr RTOS for Arm Cortex-M class MCUs. 

  • Work on sensor integration and sampling pipelines - IMUs, accelerometers, microphones, temperature sensors - over I2C, SPI, and I2S. 

  • Build, flash, and debug boards daily using West, CMake, SWD/J-Link, and serial consoles. 

  • Contribute to edge-to-cloud connectivity: Wi-Fi, MQTT over TLS, and low-power wireless protocols such as Thread and BLE. 

  • Help collect and validate sensor datasets that feed on-device machine learning models, and assist with deploying and evaluating those models on target hardware. 

Test and Tooling 

  • Write unit and integration tests alongside your feature code - we test what we ship. 

  • Build and improve bench tooling: flash/serial automation scripts, data-capture harnesses, and hardware-in-the-loop test setups. 

  • Reproduce, instrument, and root-cause bugs on real hardware, and document what you find so the next engineer doesn't hit it twice. 

Team Collaboration 

  • Participate in design discussions and code reviews - your code gets reviewed, and you review ours. 

  • Work directly with hardware and systems engineers when the bug turns out not to be in software. 

  • Present your work at the end of the internship: what you built, what you learned, and what you'd do differently. 

What we are looking for:

Required 

  • Currently pursuing a BS or MS in Computer Engineering, Electrical Engineering, Computer Science, or a related field. 

  • Solid C programming fundamentals: pointers, memory, bit manipulation, and comfort reading a datasheet. 

  • Exposure to microcontrollers through coursework, projects, clubs, or prior internships (Arduino/ESP32/STM32/Nordic all count). 

  • Basic Git fluency: branching, commits, and pull requests. 

  • Comfort with the command line and at least one scripting language (Python preferred). 

  • Curiosity and persistence. Embedded debugging rewards people who keep pulling the thread. 

  • Ability to work on-site in Arlington, TX for the duration of the internship. 

Nice to Have 

  • Coursework or projects involving an RTOS (Zephyr, FreeRTOS) or bare-metal firmware. 

  • Familiarity with communication buses (I2C, SPI, UART) and reading signals on a logic analyzer or oscilloscope. 

  • Exposure to signal processing (FFTs, filtering) or machine learning basics - our devices run inference at the edge. 

  • Experience with networking concepts: sockets, TLS, MQTT/HTTP, or wireless protocols. 

  • A personal project you can talk about in depth - hardware or software. 

What success looks like:
In your first two weeks, you will have a working development environment, a board on your desk, and your first merged pull request. By the midpoint, you will own a small feature or tooling improvement end-to-end - design, implementation, tests, and review. By the end of the internship, you will have shipped work running on live hardware in the field or on the bench test rack, and you will be able to explain the full path your data takes from sensor to cloud. 
How we work:

  • On-site, collaborative environment. We build physical hardware - presence matters. 

  • Small teams with high autonomy. Interns get real ownership, scaled to fit. 

  • Fast iteration cycles. We prototype, test, and revise quickly. 

  • Direct feedback culture. We expect candor and respect in equal measure - and we invest in people who want to grow. 

Why E-Space is right for you:

As a member of our team, you will play a crucial role in driving our success.  Our team members have a strong sense of dedication and responsibility; this includes a strong commitment to our mission to create an entirely new suite of global capabilities to improve lives, business efficiencies and build a smarter planet. This means that there will be times when extra hours, including nights and weekends, may be needed to meet critical deadlines and mission goals.  In return, we offer a dynamic work environment with opportunities for professional growth and development and the chance to make a meaningful impact in a high-growth industry.  

We want you to make the most of your journey at E-Space. That's why we support and invest in the physical, emotional and financial well-being of our team members and their families. Some of what you can expect when working at E-Space:

An opportunity to really make a difference
Sustainability at our core
Fair and honest workplace
Innovative thinking is encouraged
Competitive salaries
Continuous learning and development
Health and wellness care options
Financial solutions for the future
Optional legal services (US only)
Paid holidays
Paid time off

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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