Engineer, State Estimation (Dallas/San Diego/Boston/ DC/ San Fran)

Shield AI; Boston (MA); On-site; USD 120,000 - 250,000; Full time

Job summary

Shield AI is seeking a State Estimation Engineer to advance sensor fusion and navigation algorithms for autonomous UAVs. You will develop real-time state estimation pipelines, integrate multi-sensor data, and collaborate with autonomy, software, and hardware teams to ensure robust system performance in dynamic environments.

The role focuses on transitioning research into fielded capabilities, enabling precision navigation solutions for mission-critical applications and demanding operational

Qualifications

• Minimum 3 years of relevant experience with a bachelor’s degree; or 2 years with a master’s; or 1 year with a PhD.
• Proficient in real-time environments using C++11 or newer.
• Comfortable in Linux and using command-line tools and scripting.
• Strong written and verbal communication skills with a collaborative mindset.

Responsibilities

• Develop and implement real-time state estimation algorithms for navigation in GPS-denied or degraded environments.
• Integrate data from IMUs, GNSS receivers, visual odometry, magnetometers, barometers, and radar.
• Design sensor processing pipelines focused on accuracy and fault tolerance.
• Collaborate with autonomy, software, and hardware teams for end-to-end integration.
• Conduct simulation, lab testing, and field trials to evaluate performance.

Skills

C++11

Linux

Scripting

Communication

Algorithms familiarity

Education

Bachelor’s degree

Master’s degree

PhD

Tools

CUDA

FPGAs

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

As a State Estimation Engineer, you will play a critical role on the GNC team, contributing to the development, optimization, and deployment of advanced sensor fusion and navigation algorithms for autonomous UAV operations in dynamic and contested environments. You will help design real-time sensor processing pipelines, integrate multi-sensor data for robust state estimation, and collaborate closely with autonomy researchers, software engineers, and hardware teams to ensure high system performance and reliability.

Your work will support the transition of cutting-edge research into fielded capabilities, helping Shield AI deliver precision navigation solutions for mission-critical applications.

What you'll do

• Develop and implement real-time state estimation algorithms including inertial navigation, sensor fusion, and alternative navigation methods for GPS-denied or degraded environments.
• Integrate data from IMUs, GNSS receivers, visual odometry, magnetometers, barometers, and radar into robust estimation frameworks.
• Design sensor processing pipelines focused on accuracy, robustness, and system-level fault tolerance.
• Collaborate with autonomy, software, and hardware teams to ensure end-to-end integration of navigation and PNT systems.
• Conduct simulation, lab testing, and field trials to evaluate algorithm performance under real-world conditions.
• Stay current on advancements in state estimation and navigation technologies and help adapt new innovations into deployable solutions.

Required qualifications

• Typically requires a minimum of 3 years of relevant experience with a bachelor’s degree; or 2 years with a master’s degree; or 1 years with a PhD; or equivalent practical experience.
• Familiarity with algorithms.
• Proficient in C++11 or newer in real-time environments.
• Comfortable working in Linux, with experience using standard command-line tools and scripting.
• Strong written and verbal communication skills with a collaborative mindset.
• Demonstrated success working in fast-paced development cycles and delivering high-quality results.

Preferred qualifications

• Experience developing and deploying real-time navigation or sensor fusion algorithms using IMUs, GPS, or other sensors.
• Strong understanding of filtering and estimation techniques (e.g., Kalman filters, EKF, UKF, particle filters).
• Experience implementing inertial navigation algorithms in degraded or GPS-denied conditions.
• Exposure to visual odometry or computer vision-based navigation approaches.
• Experience optimizing code for performance on compute-constrained platforms.
• Familiarity with CUDA or hardware acceleration techniques (e.g., FPGAs).
• Experience transitioning navigation solutions from research into production environments.

$120,000 - $250,000 a year

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.

Equal Employment Opportunity Statement

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.