Shield AI
Technology
StaffEngineer,DeepLearning
Neural analysis suggests this role is
optimal for Mid candidates.
“Staff Engineer, Deep Learning at Shield AI. Skills: Deep Learning, ML Infrastructure, Distributed Systems. Design and implement deep learning models. Develop and maintain machine learning infrastructure”
Industry & Context.
Problem solving; Troubleshooting; Debugging
What They're Looking For.
Must Have
5+ years of experience in deep learning, Experience with large-scale deep learning models, Experience with deep learning frameworks, Experience with Python, Experience with C++, Experience with distributed systems, Experience with GPU computing, Experience with cloud platforms, Experience with machine learning infrastructure, Experience with large datasets
Nice to Have
PhD in a related field, Experience with PyTorch, Experience with TensorFlow, Experience with Kubernetes, Experience with CI/CD, Experience with ML Ops
What You'll Do.
Design and implement deep learning models
Develop and maintain machine learning infrastructure
Optimize deep learning training and inference
Collaborate with research scientists
Deploy models to production environments
Troubleshoot and debug issues
Stay up-to-date with the latest research
How You'll Work.
Team & Collaboration
Cross-functional teams; Research scientists
Full Job Description
## Description Founded in 2015, 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 and V-BAT and X-BAT aircraft. 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 www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube. ## 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 reconstr
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