LandOffer
Perception Engineer - Multimodal & Embodied AI (R6022)
Job details
- Work mode
- On-site
- Employment
- Full-time
- Posted
- Oct 3, 2026
- Last confirmed open
- Oct 21, 2026
What you'll need to apply
Fields this application requires
Company-specific questions
- This position may require access to information and technology that is subject to export controls, such as EAR. Are you any of the following?
- Shield AI provides technology, services, and support to the United States military and allied forces with their various missions. If selected for employment with Shield AI, your contributions will directly relate to and/or support these missions. Are there any reasons why you would not be able to fully contribute in support of the U.S. military and allied forces?
- Please state your full legal name:
- Are you a transitioning service member?
- What full time job(s) are you applying for?essay
About this role
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
Bring promising AI research into autonomous systems that operate in the real world. Shield AI’s Perception team is looking for an engineer who enjoys exploring new ideas and making them work on real hardware. You’ll help turn advances in multimodal computer vision, visual foundation models, and embodied AI into useful capabilities for autonomous aircraft and vehicles.
Working alongside researchers and autonomy engineers, you’ll evaluate promising approaches, build prototypes, and carry successful ideas into the Hivemind product. You’ll combine learned methods with established perception techniques, working through the sensor, software, and compute challenges that make edge robotics different from a benchmark.