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Shield AI is a venture-backed defense-tech company developing autonomous systems for military and civilian applications. The Hivemind Detection, Tracking, and Mapping (DTM) team builds perception capabilities that enable autonomous systems to understand objects, motion, sensors, and terrain across air, maritime, and ground domains.
You will join as a Staff Engineer on a full-stack perception product-development role, bridging research and production. Your work will span algorithm development, C++ library implementation, integration, verification, and delivery within the Hivemind SDK. You will bring deep expertise in at least one core area—such as object detection, object tracking, computer vision, image processing, sensor modeling, or sensor fusion—while working comfortably across adjacent technical areas.
Key responsibilities include:
- Evaluating emerging models and methods against representative sensor data and autonomy requirements
- Building prototypes and experiments to reveal model strengths, limitations, and practical deployment opportunities
- Combining learned and classical approaches to improve detection, tracking, geometric vision, or sensor fusion
- Optimizing and integrating capabilities for edge deployment, contributing Python and C++ software with support from experienced product engineers
- Delivering tested, documented capabilities and supporting adoption by other teams
This role emphasizes turning prototypes, research, and partner-developed technology into reusable, configurable, well-tested product capabilities. You will maintain involvement through the full lifecycle from research to production deployment.
REQUIREMENTS:
- PhD in computer vision, machine learning (ML/DL), robotics, or related field, OR equivalent record of advanced research and hands-on engineering
- Research depth in areas such as multimodal vision, visual foundation models, video understanding, open-vocabulary perception, or embodied learning
- Strong Python skills and experience with PyTorch or comparable ML framework
- Thoughtful approach to experiments, evaluation data, and understanding model failure modes
- Experience building substantial research software, interest in developing production-quality C++, and collaborative problem-solving approach
PREFERRED:
- Experience bringing research prototypes into sustained production use
- Experience with robotics, real sensors, temporal data, or multi-sensor perception
- Familiarity with vision-language models, vision-language-action models, or embodied AI
- Experience with C++, edge inference, or model optimization (ONNX, TensorRT, CUDA)
Note: You do not need to meet every preferred qualification or arrive as an expert C++ engineer. Shield AI welcomes recent PhD graduates and early-career researchers, valuing technical depth, curiosity, and enthusiasm to transfer research to business value.
