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Posted 1 mo agoFirst seen 23 d ago
Staff Deep Learning Engineer, State Estimation (R5785)
Posted by Shield AI on 26 September 2026, 37 days ago. Still on their Lever board when we checked 46 min ago. Half of Shield AI's roles come down within 45 days.
What the posting is about
Develop deep learning models for autonomous systems' motion understanding and localization in GPS-denied environments. Lead model development pipeline from data cleaning to deployment. Experience in deep learning, 3D computer vision, and geometry required.
Read out of the posting
Levelstaff
Experience asked5+ years
EmploymentFull time
LocationRemote
RemoteYes
Visa sponsorshipNot stated
SalaryNot published, and most postings do not
Posted2026-09-26
Found vialever, direct from their system
We saw it 14 days after it went up.
The posting, as the company wrote it
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:
Join Shield AI’s Hivemind SDK State Estimation & Vision team to build deep learning capabilities that help autonomous systems understand their motion and localize in the world when GPS is unavailable or unreliable.
You will work at the intersection of deep learning, 3D computer vision, and geometric estimation, developing learned components for vision-based navigation. You will own the model development pipeline—from selecting tools, defining annotation needs, and cleaning data through training, evaluation, integration support, and deployment recommendations.
Hands-on experience with Deep Learning and 3D computer vision and geometry is required; prior experience specifically in vision-based navigation is optional.
Copied from Shield AI’s own board, not rewritten.
Also open at Shield AI
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