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Shield AI is seeking a Staff Deep Learning Engineer to join its perception and autonomy team in Melbourne. You will research, design, and implement state-of-the-art deep learning solutions for computer vision, taking projects from conception through field deployment on edge devices.
Key responsibilities include architecting and developing perception capabilities for autonomous systems, deploying AI models to embedded hardware, collaborating with other deep learning engineers to scale operations, and staying current with cutting-edge research in computer vision and machine learning.
You will work with modern deep learning frameworks (TensorFlow, PyTorch, etc.) to implement novel network architectures, optimize models for edge deployment (pruning, quantization, performance tuning), and contribute to MLOps infrastructure. The role involves hands-on technical work in areas such as object detection, tracking, SLAM, 3D reconstruction, and foundation/vision-language models.
Required: 3–5 years of industry experience delivering deep learning solutions for computer vision problems. Strong expertise with CNNs and/or transformers for classification, recognition, or segmentation. Experience with foundation models and implementing architectures in modern frameworks. Bachelor's, Master's, or PhD in Computer Science or related field.
Preferred: Publications in top-tier venues (CVPR, ICCV, NeurIPS, ICML, etc.). Proficiency in C++ and Python. Deep knowledge of state-of-the-art computer vision architectures. Experience with object detection, SLAM, 3D reconstruction, behavior analysis, or vision-language models. Proven track record deploying models in embedded/production environments. MLOps experience. Mentoring experience with junior engineers.
Shield AI is a venture-backed defense-tech company developing autonomous systems, aircraft platforms, and simulation technologies to protect service members and civilians. The company operates globally with offices across the US, Europe, Middle East, and Asia-Pacific.
