Staff Deep Learning Engineer, State Estimation (R5785)

Shield AI; San Diego (CA); On-site; USD 120,000 - 210,000; Full time

Job summary

Shield AI in San Diego is seeking a developer to join the Hivemind SDK State Estimation & Vision team. You will help autonomous systems understand motion and localize when GPS is unavailable or unreliable.

You will own the model development pipeline—from tool selection, annotation needs, and data cleaning through training, evaluation, and deployment recommendations, with hands-on work in deep learning and 3D vision. Vision-based navigation experience is a plus.

Qualifications

• Hands-on experience with Deep Learning and 3D computer vision is required.
• Experience with geometry estimation is required.

Responsibilities

• Own the model development pipeline—from selecting tools, annotation needs, data cleaning, through training, evaluation, and deployment recommendations.—
• Provide integration support and deployment guidance for vision-based navigation systems.

Skills

Deep Learning

3D Computer Vision

Geometric Estimation

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:

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.