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.
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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.
Shield AI · 1mo ago
The Pilot team develops the algorithms and production software that enable intelligent systems to decide what to do and how to do it in uncertain, dynamic environments.
We are seeking an experienced Senior Staff Lab Manager to lead the design, development, operation, and long-term strategy of our engineering laboratories.
Shield AI · 7mo ago
Our next gen UAS is a next-generation, high-endurance unmanned system designed for deployment in complex, contested environments. We are seeking a Structures Design Engineer to lead the design, development, and testing of a novel launch and recovery system for our next gen UAS.
Do you enjoy working in a dynamic lab environment and being part of a design team that will impact the safety of service members and civilians? If so, we want your help designing the next generation aircraft at Shield AI.
Now, we’re building a next-generation aircraft like no other—one that will push the boundaries of innovation and performance.
As the Senior Director of Hivemind Program Finance, you will lead the Hivemind program finance activities of the team in support of program execution.
Shield AI · 27d ago
As Manager, Environmental Control Systems & Thermal, you will directly lead and develop a team of individual contributors responsible for environmental control systems, aircraft thermal management, and associated fluid and heat-transfer hardware on the X-BAT program, while…
Shield AI is seeking a Director of Proposals to lead our Business Proposals organization and turn complex deal strategies into compelling, compliant, and timely customer submissions.
Model development produces experiments, checkpoints, evaluation results and many versions of the same model. Keeping those records connected lets engineers reproduce results, compare approaches and move a trained model into use.
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