Autonomy Engineer, Navigation (R4171) at Shield AI

Dallas, Texas, United States

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Defense, Aerospace, AutonomyIndustries

Requirements

Strong proficiency in modern C++ (C++11 or newer) and professional experience developing software for embedded Linux systems
Experience designing and deploying state estimation algorithms (e.g., error state EKF, UKF) in real-world defense or aerospace applications
Familiarity with developing for constrained environments requiring deterministic timing and high reliability
Deep understanding of inertial navigation systems (INS), GNSS integration, and navigation error modeling
Expertise calibrating and integrating IMUs, GPS receivers, magnetometers, and barometric sensors with flight software
Familiarity with MATLAB or Python for prototyping is acceptable; however, primary development experience must be in C++
Preferred qualifications
Experience developing and deploying assured PNT systems for DoD customers
Expertise building digital models and simulations of navigation sensors and systems to inform hardware trade studies and mission analysis
Familiarity with alternative navigation techniques, such as celestial navigation, terrain-aided navigation, or vision-based navigation (VBN)
Experience validating and verifying navigation systems in operational test environments
Principal-level applicants are expected to demonstrate thought leadership in navigation systems and may serve as technical mentors, roadmap authors, design reviewers, or proposal authors

Responsibilities

Research and develop advanced state estimation and navigation algorithms to ensure assured Position, Navigation, and Timing (PNT) in contested environments
Design, write, and deploy production-quality C++ software for aviation platforms requiring real-time, deterministic performance
Build and maintain comprehensive unit, integration, and system-level tests to validate navigation software performance under operational constraints
Develop modeling, calibration, and simulation tools for inertial and aided navigation technologies used in airborne platforms
Participate in agile-based product planning, feature definition, capacity estimation, and cross-team collaboration
Contribute to ongoing system performance evaluation, regression analysis, and V&V (Verification and Validation) efforts

Skills

Key technologies and capabilities for this role

C++Embedded LinuxState EstimationNavigation AlgorithmsPNTInertial NavigationReal-time SoftwareUnit TestingIntegration TestingSimulation ToolsAgileAviation Platforms

Questions & Answers

Common questions about this position

What are the required qualifications for the Autonomy Engineer role?

Required qualifications include strong proficiency in modern C++ (C++11 or newer) for embedded Linux systems, experience with state estimation algorithms like EKF or UKF in defense or aerospace, familiarity with constrained environments, deep understanding of INS, GNSS integration, and expertise in calibrating IMUs, GPS, magnetometers, and barometric sensors.

What programming languages and tools are needed for this position?

Primary development requires strong proficiency in modern C++ (C++11 or newer) for embedded Linux systems, with familiarity in MATLAB or Python acceptable for prototyping.

Is this a remote position or does it require working in an office?

This information is not specified in the job description.

What is the salary or compensation for this role?

This information is not specified in the job description.

What experience makes a strong candidate for this Autonomy Engineer position?

Strong candidates have experience delivering robust navigation and state estimation for defense aviation or DoD applications, expertise in C++ for embedded Linux, and preferred experience with assured PNT systems; the role suits senior contributors to subject matter experts.

Shield AI

Develops AI and autonomous systems for defense

About Shield AI

Shield AI specializes in creating artificial intelligence and autonomous systems specifically for the defense industry. The company develops AI-powered systems, including autonomous drones, that assist military operations, especially in environments where GPS and communication may not be available. This technology allows for safer and more efficient defense operations. Shield AI differentiates itself from competitors by focusing on advanced AI capabilities and securing significant contracts with government and military clients, such as the multi-billion dollar EWAAC contract. The company's goal is to enhance operational capabilities and safety in military contexts, ultimately aiming to protect lives through its innovative solutions.

San Diego, CaliforniaHeadquarters

2015Year Founded

$772.8MTotal Funding

DEBTCompany Stage

AI & Machine Learning, DefenseIndustries

501-1,000Employees

Benefits

Medical Insurance Coverage

Long Term Disability Insurance

Health Care FSA and Dependent Care FSA

Employee Assistance Program

Subsidized Gym Membership

Pet Insurance

Competitive Compensation

Retirement Services

Life Insurance

Parental Leave

Bereavement Support

Flexible Work Hours

PTO

Paid Holidays

Commuter Benefits

Relaxed Dress Code

Yearly Swag Items

Unlimited Snacks

Bottomless Beverages

Annual Celebrations

Work From Home Benefits

Standing Desks and Widescreen Monitors

Risks

Increased competition from companies like Waymo could divert investment from Shield AI.

Geopolitical tensions may challenge the JSW Defence partnership for V-BAT production in India.

Dependency on Palantir's infrastructure may limit Shield AI's operational flexibility.

Differentiation

Shield AI's Hivemind is the first autonomous AI pilot deployed in combat since 2018.

Strategic partnerships with Palantir and JSW Defence enhance technological capabilities and market reach.

Shield AI's V-BAT drone is selected for a $198 million U.S. Coast Guard contract.

Upsides

Increased demand for autonomous systems in defense boosts Shield AI's market potential.

Successful multi-aircraft autonomous flight tests showcase advanced AI piloting capabilities.

Significant investment in robotics indicates a robust market for Shield AI's offerings.

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