Staff Engineer, State Estimation (R5783)

Shield AI
Regional
Remote

Who this role is best for

Strong fit for engineers with embedded C++ expertise and state estimation experience who can work remotely and collaborate in multidisciplinary teams.

Best fit for

  • Engineers with embedded C++ experience and a background in state estimation algorithms for autonomous systems
    — “Design and deploy production-grade C++ software for embedded robotic systems”
  • Candidates with a strong academic background in aerospace or robotics and a focus on real-world deployment
    — “M.S. in Aerospace Engineering, Electrical Engineering, Robotics, Computer Science, or a related field”
  • Individuals who can thrive in remote settings and contribute to agile, cross-functional teams
    — “Contribute to roadmap planning, feature decomposition, and agile execution alongside a multidisciplinary team”

Things to consider

  • C++ is the primary deployment language, not just a secondary skill
    — “this role demands professional C++ production deployment skills”
  • Remote work is possible, but background checks and possible reference checks are required
    — “All offers are contingent on a cleared background and possible reference check”

How to stand out

  • Emphasize real-world deployment experience of C++ in autonomous systems
    — “Ability to independently deploy high-reliability code suitable for real-world autonomous systems”
  • Showcase expertise in state estimation algorithms like EKF, UKF, or graph-based optimization
    — “Professional experience designing and implementing state estimation algorithms (e.g., EKF, UKF, Particle Filters, graph-based optimization)”
  • Highlight hands-on experience with embedded Linux platforms and low-latency applications
    — “Hands-on experience deploying low-latency C++ applications to embedded Linux platforms”
  • Demonstrate familiarity with VIO, SLAM, or multi-sensor fusion frameworks
    — “Familiarity with VIO, SLAM, or multi-sensor fusion frameworks (e.g., GTSAM, Ceres, OpenVINS)”
  • Include experience with CI pipelines and automated testing for C++ projects
    — “Strong working knowledge of CI pipelines and automated testing frameworks for C++”
Pace · Fast PacedCollaboration · MediumAutonomy · HighDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • Developed and deployed state-of-the-art state estimation algorithms
  • Built and maintained rigorous unit, integration, and system-level tests
Typical background
M.S. in Aerospace Engineering, Electrical Engineering, Robotics, Computer Science, or related fieldProfessional proficiency in modern C++

Skills & requirements

Required

C++State Estimation AlgorithmsNavigation AlgorithmsEmbedded SystemsCI PipelinesAutomated TestingReal-time Systems

Preferred

Graph-based OptimizationVision-aided Inertial Navigation SystemsNavigation Sensor CalibrationBenchmarking And System Validation

Stack & domain

C++State Estimation AlgorithmsVIOSLAMMulti-sensor Fusion FrameworksCI PipelinesAutomated Testing FrameworksIndependent DeploymentCollaborationDefense-techAutonomy SoftwareEmbedded Robotic SystemsNavigation Systems

About the role

Original posting from Shield AI via Lever

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:

Help build the intelligence that enables autonomous systems to navigate the world with confidence. In this role, you’ll develop cutting-edge estimation and navigation technology, transforming advanced algorithms into high-performance software that powers resilient autonomy in complex, real-world environments.

What you'll do::

  • Research and develop state-of-the-art state estimation and navigation algorithms to enable resilient autonomy in challenging GPS-denied environments.
  • Design and deploy production-grade C++ software for embedded robotic systems operating in dynamic, real-world environments.
  • Build and maintain rigorous unit, integration, and system-level tests to ensure system robustness and safety.
  • Develop and enhance modeling, calibration, and simulation tools for inertial and vision-based navigation systems.
  • Contribute to roadmap planning, feature decomposition, and agile execution alongside a multidisciplinary team of autonomy engineers.
  • Continuously enhance performance analysis, benchmarking, and validation pipelines to drive rapid innovation and improvement.

Required qualifications::

  • M.S. in Aerospace Engineering, Electrical Engineering, Robotics, Computer Science, or a related field; minimum 2+ years of related professional work experience if you have an M.S. degree, or 0 years if you are a new Ph.D. graduate.
  • Professional proficiency in modern C++ (C++11 or newer) and strong object-oriented design skills.
  • Hands-on experience deploying low-latency C++ applications to embedded Linux platforms.
  • Professional experience designing and implementing state estimation algorithms (e.g., EKF, UKF, Particle Filters, graph-based optimization).
  • Familiarity with VIO, SLAM, or multi-sensor fusion frameworks (e.g., GTSAM, Ceres, OpenVINS).
  • Strong working knowledge of CI pipelines and automated testing frameworks for C++.
  • Ability to independently deploy high-reliability code suitable for real-world autonomous systems.
  • Familiarity with prototyping in Python or MATLAB is welcome, but this role demands professional C++ production deployment skills. Candidates whose primary experience is in MATLAB or Python are unlikely to find this position a good fit.

Preferred qualifications::

  • Deep understanding of graph-based optimization for state estimation.
  • Experience developing vision-aided inertial navigation systems (VINS, VIO, Terrain Relative Navigation).
  • Experience with navigation sensor calibration (IMU, GPS, barometers, magnetometers, laser altimeters, cameras).
  • Experience in benchmarking and system validation for real-world navigation performance.

#LI-KC3

#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.

Source: Shield AI careers (Lever)

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