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Embedded Software Verification Engineer Jobs in Spring, TX

Polluxa, Inc.

Embedded AI/ML Developer - HP

Spring, TX · On-site

$125 - $150/hr

The engineer will work closely with hardware, firmware, software, and data science teams to translate AI/ML concepts into production-ready embedded implementations. Responsibilities include model ...

New

Hp

Embedded Firmware and Software Engineer

Spring, TX

$65K - $101K/yr

Embedded Firmware and Software Engineer Description - Job Summary This role is responsible for conducting analysis, design, programming, debugging, troubleshooting, and modification of software for ...

Tcenergy

MAOP Verification Engineer

Houston, TX · Hybrid

$129K/yr

The Opportunity The MAOP Records Verification Team is seeking an Engineer or Technologist to join ... Proficiency with engineering software and other data-related tools. Preferred Qualifications

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All JobsEmbedded Software Verification Engineer JobsEmbedded Software Verification Engineer Jobs in Spring, TX

Embedded Software Verification Engineer information

See Spring, TX salary details

$62.3K

$136.5K

$154.8K

How much do embedded software verification engineer jobs pay per year?

As of Sep 9, 2026, the average yearly pay for embedded software verification engineer in Spring, TX is $136,494.00, according to ZipRecruiter salary data. Most workers in this role earn between $117,000.00 and $154,000.00 per year, depending on experience, location, and employer.

What does an embedded software verification engineer do?

An Embedded Software Verification Engineer is responsible for ensuring that embedded software systems function correctly and meet design requirements. They create and execute tests, analyze results, and identify software defects in embedded systems such as automotive controllers, medical devices, or consumer electronics. This role typically involves working closely with software developers and hardware engineers to review code, develop test plans, and use debugging tools to validate the software’s functionality, performance, and safety. Their work is crucial for delivering reliable products that operate safely and efficiently in real-world environments.

What are the key skills and qualifications needed to thrive as an embedded software verification engineer?

To thrive as an Embedded Software Verification Engineer, a strong background in embedded systems, programming (C/C++), and software testing methodologies is essential, typically supported by a degree in computer science, electrical engineering, or a related field. Familiarity with tools such as MATLAB/Simulink, debuggers, oscilloscopes, and verification frameworks, as well as certifications like ISTQB, are commonly required. Attention to detail, problem-solving abilities, and effective communication help engineers identify issues and work collaboratively in cross-functional teams. These skills ensure the development of reliable, safe, and high-quality embedded systems in safety-critical industries.

What are some common challenges faced by embedded software verification engineers during the validation process?

Embedded Software Verification Engineers often encounter challenges such as limited hardware availability, rapidly changing requirements, and integration issues with multiple hardware and software components. Debugging in an embedded environment can be more complex due to constrained system resources and limited visibility into the hardware-software interactions. Collaborating closely with both hardware and firmware teams is essential to quickly identify and resolve defects, making strong communication and problem-solving skills crucial for success in this role.

What is the difference between Embedded Software Verification Engineer vs Embedded Software Developer?

AspectEmbedded Software Verification EngineerEmbedded Software Developer
Primary FocusVerifying and validating embedded software to ensure quality and reliabilityDesigning, coding, and implementing embedded software solutions
Skills & CertificationsKnowledge of testing tools, verification processes, embedded systems, certifications like ISTQBProficiency in programming languages (C, C++), embedded systems, software development certifications
Work EnvironmentTesting labs, development teams, quality assurance departmentsDevelopment teams, R&D labs, product engineering

While both roles require embedded systems knowledge and programming skills, the Embedded Software Verification Engineer primarily focuses on testing, validation, and ensuring software quality, whereas the Embedded Software Developer concentrates on creating and implementing embedded software solutions.

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For Embedded Software Verification Engineer jobs in Spring, TX, the most frequently searched job titles are:

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Cities near Spring, TX with the most Embedded Software Verification Engineer job openings:

Embedded Software Verification Engineer jobs near you

Embedded AI/ML Developer - HP

Spring, TX • On-site

Polluxa, Inc.
See more jobs at Polluxa, Inc.external

$125 - $150/hr

Other

This job post has expired today. Applications are no longer accepted.

Job description

Description -

The Embedded AI/ML Developer will design, develop, and optimize AI-enabled embedded software solutions for HP's commercial PC and connected device portfolio. This role focuses on deploying efficient machine learning models at the edge, integrating AI capabilities with firmware and system software, and enabling intelligent user experiences across resource-constrained platforms.

The engineer will work closely with hardware, firmware, software, and data science teams to translate AI/ML concepts into production-ready embedded implementations. Responsibilities include model optimization, inference runtime integration, performance tuning, debugging, documentation, and staying current with emerging edge AI technologies, tools, and industry best practices.

Responsibilities
  • Designs, develops, and optimizes embedded AI/ML software for edge devices, including PCs, docking solutions, displays, peripherals, and other intelligent client platforms.
  • Converts AI/ML algorithms and proof-of-concept models into efficient, production-quality embedded implementations optimized for latency, memory, power, and compute constraints.
  • Integrates machine learning inference engines, model runtimes, and AI accelerators into embedded firmware and system software environments.
  • Collaborates with cross-functional teams to define AI feature requirements, system architecture, data flow, model deployment strategy, and validation plans.
  • Profiles and tunes embedded AI workloads to improve inference performance, reduce memory footprint, improve responsiveness, and optimize power consumption.
  • Develops and maintains software interfaces between AI/ML components, firmware, device drivers, sensors, embedded controllers, and host applications.
  • Supports model compression, quantization, pruning, benchmarking, and deployment using embedded AI frameworks and hardware acceleration technologies.
  • Troubleshoots complex system-level issues involving AI inference, firmware behavior, sensor data, device communication, and platform integration.
  • Creates and maintains technical documentation, including architecture descriptions, design specifications, model deployment guides, validation procedures, and integration notes.
Education & Experience Recommended
  • Bachelor's or Master's degree in Computer Science, Computer Engineering, Statistics, Mathematics, Artificial Intelligence, Machine Learning, Robotics or a related technical discipline.
Preferred Certifications

Embedded AI/ML Engineering

  • Hands-on experience deploying AI/ML models on embedded systems, edge devices, MCUs, SoCs, NPUs, DSPs, or other constrained compute platforms.
  • Experience with model optimization techniques such as quantization, pruning, compression, TensorRT, ONNX, TFLite, or similar deployment toolchains.
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