Senior Staff Deep Learning Engineer (R5675)

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 [](https://shield.ai/). Follow Shield AI on [LinkedIn](https://www.linkedin.com/company/shield-ai), [X](https://x.com/shieldaitech), [Instagram](https://www.instagram.com/shield_ai), and [YouTube](https://www.youtube.com/@Shield_AI). ### 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 3 – 5 years - Strong understanding of using convolutional neural networks and/or transformers for object classification, recognition or segmentation - Experience working with recent Foundation Models - 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) ### Preferred qualifications: - Publication(s) in world-leading Computer Vision/Artificial Intelligence/Machine Learning conferences/journals (i.e., CVPR, ICCV, ECCV, NeurIPS, ICLR, ICML, PAMI, JMLR) - C++ and/or Python development experience - In-depth understanding of the latest deep learning network architectures for computer vision and image processing - Experience with any of the following: object detection and target tracking, simultaneous localisation and mapping (SLAM), 3D reconstruction, camera calibration, behaviour analysis, foundation models, vision language models, large multi-modal models, automated video surveillance and related fields - Experience deploying deep learning models in an embedded production context, including experience of structured and unstructured pruning, network quantization and performance tuning - Experience in maintaining and/or setting up MLOps systems and services - Experience in mentoring junior engineers/researchers in the related fields