AI Engineer, Weapon Detection

Cover
San Jose, CAFull-time$150,000–$350,000Posted Aug 27, 2026

About the role

Cover is an AI security company developing concealed weapon detection systems. Cover’s imaging technology scans students for concealed weapons in K-12 schools in the United States. Our goal is to deter school shootings by identifying concealed weapons inside of bags and underneath clothing. We are headquartered in San Jose, CA with offices in Pasadena, CA and require 5 days/week in-office work.

In order to scale to the 130,000 K-12 schools in the United States, we will need to detect weapons with fully autonomous AI models. We are looking for a deep learning engineer to take in sparse point clouds and output weapon models with low false positives. Your goal is to design weapon detection models with low latency and high accuracy to prevent school shootings.

Responsibilities:

Research, design, implement, optimize and deploy deep learning models that advance the state of the art in autonomous weapons detection models

Operate with a commercial mindset to ship working product that can detect weapons at K-12 schools in the U.S.

Develop training pipeline including synthetic data generation and validation against real sensor data

Train machine learning and deep learning models on a computing cluster to carry out visual recognition tasks, including weapon segmentation and detection

Review deep learning code and research papers, implement models and algorithms, tailor them to our specific use cases for school weapon detection, enhance internal metrics, and collaborate with downstream engineers to efficiently integrate neural networks into our scanning system

Enhance deep neural networks and their related preprocessing and postprocessing code to ensure efficient execution on an embedded device

Requirements:

Experience with PyTorch, or at least another major deep learning framework such as TensorFlow, MXNet

Deep comprehension of the foundational principles of deep learning, including layer architecture, backpropagation, and other essential concepts

Experience with object detection and classification using point cloud data from radar or lidar

Strong desire to help ship AI systems that can prevent school shootings

Due to technology export restrictions all applicants must be a US Person (citizen or legal permanent resident)

The US base salary range for this full-time position is between $150,000 - $350,000 annually.

The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.

Responsibilities

  • Research, design, implement, optimize and deploy deep learning models for autonomous weapons detection
  • Operate with a commercial mindset to ship working product for K-12 schools
  • Develop training pipeline including synthetic data generation and validation
  • Train machine learning and deep learning models on a computing cluster
  • Review deep learning code and research papers, implement models and algorithms
  • Enhance deep neural networks and related code for efficient execution on embedded devices

Qualifications

  • Experience with PyTorch or another major deep learning framework
  • Deep comprehension of foundational principles of deep learning
  • Experience with object detection and classification using point cloud data
  • Strong desire to help ship AI systems that can prevent school shootings
  • Must be a US Person due to technology export restrictions

Skills mentioned

PythonDeep LearningPyTorchComputer VisionObject DetectionMachine LearningModel DeploymentPerformance OptimizationEmbedded SystemsSensor Fusion