Integrate, characterize, calibrate, and validate multi-modal navigation sensors (IMUs, GNSS, cameras, altimeters). Develop test plans, calibration scripts, and data-processing tools; collaborate across electrical, mechanical, and software teams; support schematics, CAD, drivers, and lab-based sensor testing through production.
Founded in 2015, 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 and V-BAT and X-BAT aircraft. 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.
We are seeking a Sensor Integration Engineer to support selection, characterization, calibration, and integration of multi-modal navigation and localization sensors for the X-BAT State Estimation team. This role operates at the intersection of software, electrical, and mechanical engineering, requiring the ability to work across disciplines and directly contribute to cross-functional engineering efforts.
What you'll do:
- Support sensor integration activities from specification through production
- Develop and execute sensor characterization and calibration procedures for IMUs, GNSS receivers, cameras, and other navigation sensors
- Contribute to sensor trade studies and selection processes
- Work closely with electrical engineering, mechanical engineering, and software engineering teams on:
- Electrical interfaces, power distribution, and signal conditioning
- Mounting solutions, alignment, and thermal/vibration considerations
- Software interfaces, drivers, data acquisition, and calibration implementation
- Participate in design reviews across EE/ME/SW disciplines, providing interdisciplinary perspective and coordination
- Develop and execute test plans for sensor performance characterization and validation
- Document sensor characteristics, trade studies, and integration requirements
- Develop or modify calibration scripts and data processing tools
- Support development of calibration procedures and tooling
- Debug issues spanning hardware-firmware-software boundaries
- Review and contribute to schematics, CAD models, and code as necessary
Sensor Selection, Integration & Characterization
Cross-Functional Collaboration
Technical Contributions
Required qualifications:
- BS in Electrical Engineering, Mechanical Engineering, Aerospace Engineering, Physics, or related field
- 1-4 years of relevant experience (new grads with strong cross-functional internship/project experience will be considered)
- Demonstrated ability to work across at least two of: electrical, mechanical, software domains
- Ability to obtain a S//SAR level security clearance desired.
- Understanding of sensor measurement principles and error sources
- Ability to read and understand electrical schematics and/or mechanical drawings
- Basic proficiency in scripting or programming for data analysis (Python, MATLAB, or similar)
- Familiarity with sensor communication protocols (SPI, I2C, UART, CAN, etc.)
- Hands-on experience with lab equipment and sensor testing
- Comfortable learning and working outside primary discipline
- Ability to communicate effectively with engineers from different backgrounds
- Willingness to engage with hardware, firmware, and software aspects of sensor systems
- Strong analytical and problem-solving skills across multiple domains
Education & Experience
Technical Skills
Cross-Functional Aptitude
Preferred qualifications:
- Experience with navigation or localization sensors (IMUs, GNSS, cameras, altimeters, etc.)
- Exposure to sensor calibration or characterization activities
- Familiarity with embedded systems or real-time software
- Understanding of coordinate transformations or sensor fusion concepts
- Experience with automated testing or data acquisition systems
- Knowledge of aerospace environmental testing or standards
Work environment:
- Collaborative team environment working with EE, ME, and SW engineers
- Hands-on lab work combined with analysis and documentation
- Occasional travel for team and supplier coordination or testing support
#LI-SM1
#LC
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.
###
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.
Similar Jobs at Shield AI
Aerospace • Artificial Intelligence • Machine Learning • Robotics • Software
Manage end-to-end production and execution of multi-channel paid media campaigns, coordinate agencies and internal teams, oversee website and landing page operations, handle asset formatting/trafficking/versioning, and build process, workflow, automation, and AI-driven optimizations to improve campaign speed, accuracy, and scalability.
Top Skills:
AIAsanaAutomation ToolsCampaign Management SystemsCms PlatformsCtvGoogle AdsJIRALinkedin Campaign ManagerProgrammatic AdvertisingYoutube
Aerospace • Artificial Intelligence • Machine Learning • Robotics • Software
Lead integration, validation, and fielding of advanced weapon capabilities on X-Bat across the full lifecycle. Define system behaviors and architectures, coordinate cross-functional integration, support lab/ground/flight tests, perform troubleshooting and root-cause analysis to reduce integration risk and accelerate capability delivery.
Top Skills:
Cameo Systems ModelerHilMbseMil-Std-1553Mil-Std-1760Sil
Aerospace • Artificial Intelligence • Machine Learning • Robotics • Software
Lead design and development of advanced electrical systems for autonomous aircraft, including circuit and subsystem design, part selection, schematic capture, simulation, verification, debugging, and production releases. Integrate embedded systems and sensors for autonomy, coordinate cross-functional teams, mentor engineers, define technical requirements, and develop automated test solutions to improve hardware reliability and production readiness.
Top Skills:
AnalogDigitalEmbedded SystemsFirmwareFpgasMicrocontrollersPower ManagementRadiosSensorsServos
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
