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Embedded Systems Engineer Entry Level Jobs in Texas

TerraFirma

Robotics Engineer - Embedded Software

Austin, TX · On-site

$130K - $171K/yr

Design and architect firmware and low-level code for embedded systems and microcontrollers ... S. in Computer Engineering, Computer Science, Electrical Engineering, or a closely related field ...

Chipton Ross

Embedded Software Engineer

Grand Prairie, TX · On-site

$113.22/hr

Job #219167 Chipton-Ross is seeking multiple Embedded Software Engineers for a contract opportunity ... Proficiency in Linux systems and Real-Time Operating Environment * Must have previous HardWare-In ...

Lockheed Martin Corporation

$54.25 - $66.50/hr

You will be a Cyber Systems Security Engineer in the Program Protection Organization. Our organization oversees all aspects of Anti-Tamper and embedded Cybersecurity across Missiles and Fire Control.

InfoVision, Inc.

Embedded C/C++ Developer

Dallas, TX · On-site

Must have worked on embedded systems * Must have good knowledge of data structures and algorithms * Must have good knowledge of network programing * Good debugging skills * Working knowledge of Git ...

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Embedded Systems Engineer Entry Level information

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$127.9K

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How much do embedded systems engineer entry level jobs pay per year?

As of Aug 13, 2026, the average yearly pay for embedded systems engineer entry level in Texas is $127,892.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,900.00 and $152,300.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an entry-level embedded systems engineer?

To thrive as an Entry-Level Embedded Systems Engineer, you need a solid understanding of C/C++ programming, microcontroller architectures, and basic electronics, usually backed by a bachelor's degree in electrical engineering, computer engineering, or a related field. Familiarity with tools such as oscilloscopes, debuggers, integrated development environments (IDEs) like Keil or Eclipse, and version control systems like Git is typical. Strong problem-solving skills, attention to detail, and effective teamwork help you excel in this collaborative and detail-oriented environment. These competencies are crucial for developing reliable embedded solutions that meet technical requirements and project deadlines.

What does an entry-level embedded systems engineer do?

As an entry-level embedded systems engineer, you carry out your duties under the supervision of an experienced embedded systems engineer to learn the necessary responsibilities and skills for the job. Entry-level embedded systems jobs include tasks that focus on hardware and software design and the components that go along with them. You design, troubleshoot, and test hardware and software, electronic circuits, mechanical equipment and machines, and other systems related to computers and computer equipment. Entry-level embedded systems engineer roles are usually for recent or soon-to-be graduates of a bachelor’s degree program in computer science, computer engineering, or a similar field.

More about Embedded Systems Engineer Entry Level jobs
What are the most commonly searched types of Embedded Systems Engineer jobs in Texas? The most popular types of Embedded Systems Engineer jobs in Texas are:
What are popular job titles related to Embedded Systems Engineer Entry Level jobs in Texas? For Embedded Systems Engineer Entry Level jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Embedded Systems Engineer Entry Level jobs in Texas look for? The top searched job categories for Embedded Systems Engineer Entry Level jobs in Texas are:
What cities in Texas are hiring for Embedded Systems Engineer Entry Level jobs? Cities in Texas with the most Embedded Systems Engineer Entry Level job openings:
Embedded Systems Engineer Entry Level jobs near you
Infographic showing various Embedded Systems Engineer Entry Level job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 86% Full Time, 9% Part Time, 3% Contract, and 1% Nights. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $127,892 per year, or $61.5 per hour.

Sr. Embedded Machine Learning Engineer

Allen Control Systems

Austin, TX • On-site

$195K - $261K/yr

Full-time

Medical, Dental, Vision, PTO

Re-posted 4 days ago

Job description

Company Overview
Allen Control Systems (ACS) is a cutting-edge defense startup founded by two former Navy electrical engineers with a proven track record in robotics and software. We are developing an autonomous gun turret using advanced computer vision and control systems to precisely detect, track, and neutralize enemy drones.
With an engineering-first culture, ACS values technical excellence and innovation. Backed by our founders' successful exits from two previous ventures acquired for a combined $180M in 2022, we are committed to ensuring that the groundbreaking technologies we develop will have a real-world impact.
About The Role
We are looking for a Senior Embedded Machine Learning Engineer to own the end-to-end process of taking trained ML models and deploying them efficiently onto resource-constrained edge hardware. This role sits at the intersection of machine learning, embedded systems, and hardware engineering. You will integrate, convert, and optimize models to run within strict constraints on latency, memory, power, and thermal budget, and build the supporting C++ infrastructure that hosts them on device. You will partner closely with the CVML team who build the models, the embedded and firmware teams who own the device, and the product team who define performance targets. Success means models that are not just accurate in the lab but fast, small, and dependable in the field.
What You'll Do
  • Apply quantization, pruning, knowledge distillation, operator fusion, and graph optimization to shrink models and reduce inference cost while protecting accuracy; convert trained models into edge-deployable formats using ONNX and TensorRT.
  • Profile inference on target accelerators including GPUs, NPUs, DSPs, and FPGAs; measure latency, throughput, memory footprint, and power consumption, then drive the changes needed to hit performance targets.
  • Design, write, and maintain the C++ application code that hosts inference on device, including pre- and post-processing pipelines, data and memory management, threading, and interfaces to the rest of the embedded system; ensure the combined model and C++ stack meets real-time constraints and fits within device memory budget.
  • Build test harnesses to verify on-device accuracy against reference results and catch regressions from optimization or quantization; contribute to tooling for packaging, versioning, and delivering model updates to deployed devices.
  • Set best practices for edge deployment, review designs and code, and mentor other engineers on optimization and embedded ML techniques; work closely with research, firmware, and product teams to set realistic performance targets and feed hardware constraints back into model design.

What You'll Need
  • 10+ years of professional software or systems engineering experience, including at least 2 years focused on deploying ML models to embedded or edge devices; Bachelor's or Master's degree in Computer Science, Electrical Engineering, Computer Engineering, or equivalent practical experience.
  • Very strong C++ proficiency; working knowledge of CUDA; hands-on experience with PyTorch and at least one edge inference runtime such as TensorFlow Lite, ONNX Runtime, or TensorRT.
  • Practical experience with model optimization techniques including post-training quantization, quantization-aware training, pruning, and distillation; demonstrated ability to profile and optimize for latency, memory, and power on constrained hardware.
  • Working knowledge of embedded or edge platforms such as NVIDIA Jetson, Qualcomm, ARM Cortex, or comparable NPUs and SoCs, and of Linux or an RTOS; solid grasp of computer architecture concepts relevant to inference including memory hierarchy, fixed-point arithmetic, and accelerator offload; domain experience in computer vision or sensor processing on device.

You'll Stand Out
  • Hands-on experience deploying computer vision models for detection or tracking tasks on embedded or edge hardware.
  • Experience with NVIDIA Jetson specifically, including TensorRT optimization and deployment on Jetson platforms.
  • Background in defense, autonomous systems, or robotics where real-time reliability matters.
  • Experience building or contributing to model update and OTA delivery pipelines for deployed edge devices.

What We Offer
  • Competitive salary
  • ACS Equity Package
  • Health, Dental, Vision Insurance
  • Paid Time Off

Allen Control Systems is an Equal Opportunity Employer, providing equal employment opportunities to all employees and applicants for employment. Allen Control Systems prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. #LI-AS1

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