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Temporary Embedded Engineer Jobs in Ashburn, VA (NOW HIRING)

Shield AI

Staff Hardware Recruiter

Washington, DC

$120K - $180K/yr

Proven success recruiting Electrical Engineers, Power Electronics Engineers, Embedded Hardware ... Pay within range listed above + temporary benefits package (applicable after 60 days of employment ...

Shield AI

Staff Hardware Recruiter

Washington, DC · On-site

$120K - $180K/yr

Proven success recruiting Electrical Engineers, Power Electronics Engineers, Embedded Hardware ... Pay within range listed above + temporary benefits package (applicable after 60 days of employment ...

NTT DATA, Inc.

IoT / Edge Software Engineer

Bethesda, MD · On-site

$68.08 - $141.83/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The position requires hands‑on experience with embedded Linux, MQTT messaging, and integration ... If the position offered in temporary, the position will not be eligible for incentive compensation.

New

T-Mobile

Senior Engineer, Device Hardware & Fleet

Bethesda, MD · On-site

$108K - $194K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... tablets, phones, embedded systems) (Required) * 4-7 years experience Hands-on experience ... At T-Mobile, employees in regular, non-temporary roles are eligible for an annual bonus or periodic ...

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All JobsEmbedded Engineer JobsTemporary Embedded Engineer JobsTemporary Embedded Engineer Jobs in Ashburn, VA

Temporary Embedded Engineer information

See Ashburn, VA salary details

$63.9K

$140.4K

$196.3K

How much do temporary embedded engineer jobs pay per year?

As of Aug 20, 2026, the average yearly pay for temporary embedded engineer in Ashburn, VA is $140,377.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,000.00 and $167,200.00 per year, depending on experience, location, and employer.

What is a temporary embedded engineer?

Temporary Embedded Engineers are professionals hired on a short-term contract basis to design, develop, or troubleshoot embedded systems, which are specialized computing systems integrated into larger devices or products. They typically work on projects requiring expertise in hardware, firmware, or software for embedded platforms, and may assist with prototyping, testing, or debugging during critical phases. Temporary Embedded Engineers are often brought in to address immediate needs, cover staff shortages, or provide specialized skills for a specific duration.

What are some common challenges temporary embedded engineers face when joining a new project mid-development?

Temporary Embedded Engineers often encounter challenges such as quickly understanding existing codebases, aligning with established development processes, and integrating into teams with established workflows. Adapting to proprietary hardware or unfamiliar toolchains can also be demanding. Success in the role often depends on strong communication skills, the ability to swiftly learn new systems, and proactively seeking clarification from team members to ensure seamless project contribution.

What are the key skills and qualifications needed to thrive as a temporary embedded engineer, and why are they important?

To thrive as a Temporary Embedded Engineer, you need expertise in embedded systems design, proficiency in programming languages such as C/C++, and a relevant engineering degree. Familiarity with development tools like oscilloscopes, logic analyzers, debuggers, and version control systems, as well as experience with real-time operating systems (RTOS), is typically required. Strong problem-solving skills, adaptability, and effective communication are essential soft skills for quickly integrating into new teams and projects. These competencies enable rapid contribution to project goals, efficient troubleshooting, and seamless collaboration in fast-paced, time-limited assignments.

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

AspectTemporary Embedded EngineerEmbedded Software Developer
CredentialsTypically requires a degree in Electrical Engineering, Computer Engineering, or related fields; certifications like ARM or IoT are a plusUsually holds a degree in Computer Science, Electrical Engineering, or related; certifications vary but often include embedded systems or programming languages
Work EnvironmentContract-based, often on-site or remote, working on specific projects for limited durationsFull-time or freelance, working on software development, debugging, and system integration
Industry UsageCommon in manufacturing, automotive, aerospace, and IoT sectorsPrevalent in consumer electronics, robotics, and embedded systems companies

The main difference is that a Temporary Embedded Engineer is hired for short-term projects focusing on embedded hardware and firmware, while an Embedded Software Developer typically works on long-term software development within embedded systems. Both roles require similar technical skills but differ mainly in employment type and project scope.

Are temporary embedded engineers in demand?

Temporary embedded engineers are in demand due to the growing need for specialized skills in hardware and firmware development across industries such as automotive, aerospace, and consumer electronics. Employers seek professionals with experience in C/C++, real-time operating systems, and debugging tools, making these roles valuable for project-based and short-term assignments.

What are the most commonly searched types of Embedded Engineer jobs in Ashburn, VA?

The most popular types of Embedded Engineer jobs in Ashburn, VA are:

What are popular job titles related to Temporary Embedded Engineer jobs in Ashburn, VA?

For Temporary Embedded Engineer jobs in Ashburn, VA, the most frequently searched job titles are:

What job categories do people searching Temporary Embedded Engineer jobs in Ashburn, VA look for?

The top searched job categories for Temporary Embedded Engineer jobs in Ashburn, VA are:

Temporary Embedded Engineer jobs near you

Staff Software Engineer, Perception (R5421)

Shield AI

Washington, DC • On-site

$195K - $292K/yr

Full-time

Posted 22 days ago

Job description

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube. 

The Hivemind Solutions Perception team develops the next generation of perception capabilities for autonomous systems by combining state-of-the-art machine learning with the proven foundations of computer vision. The team advances how autonomous platforms understand and interpret the world by developing vision, vision-language (VLM), and vision-language-action (VLA) models that tackle core perception challenges such as object understanding, scene interpretation, and mission-relevant environmental awareness. Working at the intersection of research and production, our engineers build the data pipelines, supervised fine-tuning (SFT) workflows, evaluation frameworks, and deployment infrastructure needed to transform cutting-edge AI research into reliable, mission-ready perception capabilities.
 
In this role, you'll lead the technical development of advanced machine learning solutions that define the future of perception for autonomous systems. You'll own the team's most challenging technical problems, drive architecture and model development across multiple efforts, and influence how foundation models are adapted, evaluated, and deployed for real-world autonomy. Working closely with researchers, perception engineers, autonomy engineers, and platform teams, you'll bridge cutting-edge AI research with scalable production systems while mentoring engineers and raising the technical bar across the organization.
What You'll Do:

Model Development – Design, train, fine-tune, and maintain state-of-the-art vision, vision-language, and vision-language-action models that improve perception and decision-making for autonomous systems. 

Data Pipelines & Model Training – Build scalable data pipelines, supervised fine-tuning (SFT) workflows, and evaluation loops that continuously improve model performance on mission-relevant tasks. 

Model Deployment & Optimization – Deploy and optimize machine learning models for embedded hardware using technologies such as ONNX, TensorRT, and hardware-accelerated inference frameworks. 

Perception & Autonomy Applications – Apply modern machine learning techniques to solve challenging perception and autonomy problems across aerial and other autonomous systems operating in complex, real-world environments. 

Research-to-Production – Translate cutting-edge machine learning research into production-ready capabilities by balancing model performance, robustness, computational efficiency, and operational reliability. 

Cross-functional Collaboration – Partner closely with perception, autonomy, platform, and software engineering teams to integrate machine learning capabilities into mission-ready autonomous systems. 

Model Evaluation & Validation – Develop benchmarks, testing methodologies, and evaluation frameworks to measure model performance, identify failure modes, and guide future improvements. 

Continuous Improvement – Improve training infrastructure, developer tooling, deployment workflows, and model lifecycle management to accelerate experimentation and production delivery. 

Required Qualifications:

  • Typically requires a minimum of 7 years of related experience with a Bachelor’s degree; or 6 years and a Master’s degree; or 4 years with a PhD; or equivalent work experience.

  • Expertise of machine learning fundamentals. 

  • Experience training an deploying ML models for computer vision in a production setting. 

  • Strong understanding of 3D vision problems/algorithms. 

  • Experience with machine learning frameworks such as PyTorch and TensorFlow. 

  • Demonstrated expertise in deploying models using TensorRT and ONNX. 

  • Proficiency in C++ and Python. 

  • Strong analytical and problem-solving skills, with the ability to translate research into practical applications. 

  • Ability to obtain a SECRET clearance 
Preferred Qualifications:

  • Experience with developing autonomous systems for defense customers. 

  • Experience with training/finetuning vision-language models, vision-language-action models, and/or world models.  

  • Contributions to open-source projects in machine learning or computer vision. 

  • Track record of publications in leading computer vision and robotics conferences and journals (e.g., CVPR, ICCV/ECCV, RAL, ICRA).

#LI-DS-1
#LD

Full-time regular employee offer package:
Pay within range listed + Bonus + Benefits + Equity
 
Temporary employee offer package:
Pay within range listed above + temporary benefits package (applicable after 60 days of employment)
 
Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information.
 
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Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know. 

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.