Staff Engineer, Deep Learning

About Shield AI

Shield AI is a venture-backed defense technology company focused on safeguarding service members and civilians through intelligent systems. Their offerings include Hivemind autonomy software, V-BAT and X-BAT aircraft, along with Aechelon simulation and synthetic reality products. Operating across multiple continents, Shield AI's technologies actively support global missions.

Role Overview

Join an innovative team shaping the future of perception technology for both autonomous and non-autonomous platforms. This role focuses on creating cutting-edge deep learning solutions that operate in real-time at the edge to tackle practical perception challenges.

Key Responsibilities

• Design, research, and develop advanced perception capabilities, transforming ideas into deployable field solutions.
• Deploy and maintain AI software stacks on edge computing devices.
• Collaborate with fellow deep learning engineers to build scalable tools for deep learning operations.
• Remain current with academic and industry research, actively engaging in R&D projects.

Required Qualifications

• 3 to 5 years of professional experience delivering deep learning models for computer vision applications.
• Solid expertise with convolutional neural networks and/or transformer architectures for tasks such as object classification, recognition, or segmentation.
• Familiarity with recent foundational AI models.
• Hands-on experience implementing novel deep learning architectures using frameworks like TensorFlow, PyTorch, or Caffe.
• Relevant degree in Computer Science or a related discipline (Bachelor’s, Master’s or PhD).

Preferred Skills

• Publications in top-tier computer vision or AI research venues (e.g., CVPR, ICCV, ECCV, NeurIPS, ICLR).
• Proficiency in C++ and/or Python programming.
• Deep understanding of cutting-edge neural architectures for vision and image processing.
• Experience with object detection, target tracking, SLAM, 3D reconstruction, camera calibration, behavior analysis, foundation and vision-language models, large multimodal systems, and video surveillance applications.
• Background in deploying deep learning on embedded devices, including pruning, quantization, and performance optimization techniques.
• Experience setting up or maintaining MLOps infrastructures.
• Ability to mentor junior engineers and researchers in relevant areas.

Additional Information

Shield AI values diversity and is an equal opportunity employer. All qualified candidates will be considered regardless of race, gender, age, disability, or other protected status. They support accommodations for candidates with disabilities. AI tools may be used in the recruitment process to assist with application review, but human judgment guides all hiring decisions.