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Temporary Embedded Engineer Jobs in Texas (NOW HIRING)

Shield AI

Staff Engineer, Data Analysis (R5290)

Dallas, TX · On-site

$150K - $220K/yr

Work with Software, GNC, Embedded, Flight Test, Systems, Production, Quality, and Operations teams ... Pay within range listed above + temporary benefits package (applicable after 60 days of employment ...

Shield AI

Ground System Software Engineer (R4787)

Dallas, TX · On-site

$110K - $200K/yr

Collaborate closely with teams across autonomy, embedded systems, human factors, and UX to deliver ... Pay within range listed above + temporary benefits package (applicable after 60 days of employment ...

Shield AI

Ground System Software Engineer (R4787)

Dallas, TX · On-site

$110K - $200K/yr

Collaborate closely with teams across autonomy, embedded systems, human factors, and UX to deliver ... Pay within range listed above + temporary benefits package (applicable after 60 days of employment ...

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Temporary Embedded Engineer information

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 Texas?

The most popular types of Embedded Engineer jobs in Texas are:

What are popular job titles related to Temporary Embedded Engineer jobs in Texas?

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

What job categories do people searching Temporary Embedded Engineer jobs in Texas look for?

The top searched job categories for Temporary Embedded Engineer jobs in Texas are:

Temporary Embedded Engineer jobs near you

Staff Engineer, Data Analysis (R5290)

Shield AI

Dallas, TX • On-site

$150K - $220K/yr

Full-time

Re-posted 8 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. 

Job Description:

We’re looking for a Staff Engineer to lead V-BAT’s fleet data analysis efforts. The V-BAT system produces rich data from real-world flight tests, fielded aircraft, production activity, and simulation runs.  

You will own the analysis pipelines, tooling, standards, and metrics that help the team understand fleet-wide system performance derived from information from software and hardware systems. You will facilitate deep studies into flight-critical sensor performance, navigation, communications, and other key aircraft behaviors. You will work closely with DevOps, Flight Software, Flight Test, Production, Quality, and Operations teams to turn complex aircraft data into actionable engineering insight. 

What you'll do:
  • Lead the technical strategy for V-BAT fleet data analysis across fielded aircraft, flight test, simulation, production, and quality workflows 
  • Own and improve the pipelines that transform raw flight, simulation, and fleet data into reliable engineering metrics, reports, and analysis products 
  • Conduct fleet-wide studies to identify trends in hardware quality, system performance, reliability, and operational behavior 
  • Analyze flight-critical sensor performance, GNSS-denied navigation performance, communications behavior, and other aircraft subsystems that are critical to mission success 
  • Standardize the team’s analysis methods across online tools, Jupyter notebooks, automated Python scripts, and legacy Matlab workflows 
  • Define best practices for analysis methods, data review, documentation, validation, reproducibility, and contribution workflows 
  • Build automated Python workflows that make high-value metrics easily accessible to engineering, production, quality, and leadership teams 
  • Partner with DevOps to build, deploy, maintain, and scale the infrastructure required for automated analysis pipelines and dashboards 
  • Work with Software, GNC, Embedded, Flight Test, Systems, Production, Quality, and Operations teams to define metrics that reflect aircraft performance and product health 
  • Support anomaly investigations, root-cause analysis, release readiness, production quality improvements, and customer-impacting fleet investigations with rigorous data analysis 
  • Mentor engineers on effective data analysis practices and raise the quality bar for data-driven engineering decisions across the V-BAT team 
Required qualifications:
  • 5+ years of relevant experience with a Bachelor’s degree in Computer Science, Data Science, or a related technical field 
  • Strong Python skills and experience building data analysis tools, automated analysis workflows, or data pipelines 
  • Experience analyzing data from fielded physical products such as aerospace systems, automotive systems, robotics platforms, commercial electronics, IoT devices, industrial equipment, or similarly complex real-world systems 
  • Experience working with large, messy datasets from deployed products, test events, simulations, production systems, or operational environments 
  • Ability to translate ambiguous engineering questions into structured analysis, sound conclusions, and clear recommendations 
  • Strong communication skills and the ability to influence cross-functional engineering, production, quality, and operations teams 
Preferred qualifications:
  • Experience with flight test data, aircraft telemetry, UAVs, robotics, autonomy, embedded systems, GNC, navigation systems, communications systems, or aerospace sensor suites 
  • Experience with Matlab, Jupyter, or similar analysis and visualization tools 
  • Experience building production-quality dashboards, automated reports, data products, or fleet-health monitoring systems 
  • Experience with databases, cloud storage, data lake architectures, time-series databases, telemetry systems, or data cataloging 
  • Experience with anomaly detection, trend analysis, statistical process control, reliability analysis, regression detection, or automated validation of complex systems 
#LI-SM1
#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.