Location
In office (Melbourne)
Seniority
Middle
Employment
Full-Time
Confirmed on the employer's own hiring board on Oct 29, 2026. First seen by Alion on Jun 11, 2026. Shield AI scores B on the Alion truth index.
Overview
Company
Impact
Profile match
Shield AI is an American defence technology company founded in 2015 that builds autonomy software and uncrewed aircraft for military missions. Its Hivemind autonomy stack lets aircraft fly, navigate and complete objectives without GPS, a remote pilot or a communications link, which matters in contested environments where those links are jammed. Headquartered in San Diego, California, the company fields the V-BAT vertical take-off aircraft with United States and allied forces, licenses Hivemind to other manufacturers and is developing the X-BAT jet for high-end missions.
Job Description:
Join Our Team: Shape the Future of Perception Technology !
Are you ready to revolutionize the world of perception capabilities for both autonomous and non-autonomous platforms?
At the forefront of innovation, we are pushing the boundaries of what’s possible, turning cutting-edge insights into real-time, deep-learning-based solutions to solve practical perception challenges on the edge. Your skills will play a key role in driving transformative solutions that redefine the future.
Be part of a dynamic team where innovation meets impact. Let’s shape the future together!
What you'll do:
- Research, design and implement state-of-the-art perception capabilities, taking ideas from conception into world-class field solutions
- Work with and deploy our AI stack to edge devices
- Work in collaboration with the other deep learning engineers to architect and develop tools help to scale up our deep learning operations
- Stay abreast with the literature and actively involve in various R&D project(s)
Required qualifications:
- Demonstrable experience in delivering deep-learning-based solutions to solve computer vision problems with industry-based experience between < 1 year
- Strong understanding of using convolutional neural networks and/or transformers for object classification, recognition or segmentation
- Experience with implementing novel deep learning network architectures using existing frameworks (TensorFlow, Caffe, PyTorch or similar)
- Relevant tertiary qualifications (Bachelors/Master/PhD in Computer Science or related fields)
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