Staff Deep Learning Engineer

Company Overview

Shield AI is a venture-backed defense technology company focused on protecting military personnel and civilians through intelligent systems. Their product portfolio includes the Hivemind autonomy software, V-BAT and X-BAT aircraft platforms, and Aechelon synthetic reality and simulation tools. Operating globally with facilities in the US, Europe, the Middle East, and Asia-Pacific, Shield AI's technology actively supports operations worldwide.

Role Summary

Join a pioneering team dedicated to advancing perception technology for both autonomous and non-autonomous systems. This role offers the chance to innovate by transforming deep learning research into real-time, deployable solutions that address practical perception challenges at the edge.

Key Responsibilities

• Conduct research, design, and implement advanced perception technologies moving concepts to deployment-ready field solutions.
• Deploy and integrate AI software stacks on edge devices.
• Collaborate with fellow deep learning engineers to architect and build scalable tools for deep learning operations.
• Continuously engage with the latest research literature and participate in diverse R&D initiatives.

Essential Qualifications

• 3 to 5 years of industry experience delivering deep learning solutions for computer vision challenges.
• In-depth expertise with convolutional neural networks and/or transformers for tasks such as object classification, recognition, and segmentation.
• Familiarity with recent Foundation Models.
• Proficient in developing novel deep learning architectures utilizing frameworks like TensorFlow, Caffe, PyTorch, or similar.
• Relevant academic credentials including a Bachelor’s, Master’s, or PhD in Computer Science or closely related fields.

Preferred Qualifications

• Published works in top-tier Computer Vision, Artificial Intelligence, or Machine Learning venues (e.g., CVPR, ICCV, ECCV, NeurIPS, ICLR, ICML, PAMI, JMLR).
• Programming experience in C++ and/or Python.
• Advanced knowledge of contemporary deep learning network architectures for vision and image processing.
• Experience with object detection and tracking, SLAM, 3D reconstruction, camera calibration, behavior analysis, foundation and vision-language models, large multi-modal models, automated video surveillance, and related fields.
• Proven record deploying deep learning models in embedded production environments, including techniques such as pruning, network quantization, and performance optimization.
• Familiarity with establishing and maintaining MLOps infrastructures and services.
• Experience mentoring less-experienced engineers or researchers within the domain.

Compensation and Equal Employment Opportunity

Compensation varies based on skills, experience, certifications, and location. Offers are contingent upon successful background and reference verification.

Shield AI is an equal opportunity employer committed to fostering diversity and inclusion. Accommodations for disabilities are available upon request.

Use of AI in Hiring

AI tools may assist with application review and assessment to support the hiring process; however, final employment decisions are made by people.