AI large model application layer algorithm engineer

Job Responsibilities:

1. R & D and optimization of anti-drone AI large model

• Responsible for the algorithm design and engineering implementation of large AI models (such as multi-modal perception, target prediction, decision generation, etc.) in the counter-drone (C-UAS) field, and promote the intelligent upgrade of the entire process of drone detection, identification, tracking, and countermeasures.

• Develop large model applications based on drone behavior characteristics (such as flight trajectory, electromagnetic signals, and image features) to improve the accuracy and real-time performance of anti-drone systems in complex environments (cities, low altitudes, and dense interference).

2. MultiModal Machine Learning Data Fusion and Intelligent Decision Making

• Integrate multi-source sensor data such as radar, photoelectric, electromagnetic, and acoustic, and build a multi-modal large model fusion algorithm to achieve dynamic classification and threat level assessment of drone targets.

• Design an AI-driven countermeasure strategy generation module that combines drone behavior prediction with real-time environmental information to output optimal countermeasure instructions (e.g., jamming, trapping, physical strikes).

3. Lightweight large model and edge deployment

• Optimize the deployment efficiency of large models on embedded devices (such as Edge Computing nodes and drone countermeasure end points) and reduce the consumption of computing resources to meet the requirements of anti-drone systems for low latency and high reliability.

• Research model quantization, pruning, distillation and other technologies to improve the real-time inference ability of the model at the edge and ensure the stable operation of the anti-drone system in complex environments.

4. Anti-unmanned business intelligent process design

• Participate in the whole process design of anti-drone system from Data Acquisition, Model Training to deployment and application, and promote the deep integration of AI technology into anti-drone business (such as automatic threat warning and intelligent countermeasure scheme generation).

• Develop standardized interfaces and toolchains for anti-drone AI large models to support rapid iteration and cross-platform deployment according to industry requirements.

5. Technical research and cutting-edge research

• Track the cutting-edge technologies of AI large models in the field of anti-drone (such as Transformer + radar signal processing, few-shot learning, reinforcement learning decision-making), carry out innovative algorithm research, and improve the technical barriers of anti-drone systems.

• Collaborate with universities and research institutions to promote technological breakthroughs of the anti-drone AI large model in scenarios such as complex electromagnetic confrontation and dynamic target tracking.

Job Requirements

1. Education Background and Skills

• Master's degree or above in computer, automation, electronic engineering, signal processing or related majors, doctorate preferred.

• Proficient in Python/C++, familiar with deep learning frameworks such as TensorFlow/PyTorch, and have more than 3 years of R & D experience in large AI models (such as LLM, Multi-modality model).

2. Core Competence

• Have the ability to fuse multi-modal data (such as radar + image + electromagnetic signal) and implement large model engineering, and be familiar with technologies such as model quantization and edge deployment.

• Familiar with anti-drone system architecture, understand drone communication protocol, electromagnetic characteristics, flight trajectory modeling, and those with relevant project experience are preferred.

• Master cutting-edge AI technologies such as reinforcement learning, few-shot learning, and self-supervised learning, and be able to conduct innovative algorithm research for anti-drone scenarios.

3. Experience Requirements

• Led at least one large AI model implementation project in anti-drone, target tracking, intelligent decision-making and other fields, with full process experience from requirements analysis to deployment.

• Familiar with the integration and debugging of sensors (such as radar, photoelectric equipment) and countermeasure equipment (such as jammers, traps) in anti-drone systems.

4. Soft Skills

• Excellent cross - team collaboration skills, able to work closely with hardware engineers, system engineers, Product Managers, etc., to promote the implementation of AI technology in actual business.

• Have a keen insight into the technological development in the field of anti-drone, and be able to quickly transform academic achievements into business value.

4. Bonus Items

1. Have published papers or patents in the fields of anti-drone, intelligent security, military AI, etc.

2. Familiar with relevant regulations and industry standards for drone countermeasures (such as electromagnetic interference and airspace management).

3. Have experience in developing edge AI chips (such as NVIDIA Jetson and Huawei Ascend), or be familiar with deployment tools such as ROS and Docker.

5. Position Value

• Participate in the core R & D of the AI large model in the anti-drone field, and promote the leapfrog upgrade of the anti-drone system from "traditional detection" to "AI intelligent decision-making".

• Work with the top team to tackle technical problems in complex scenarios such as low-altitude safety and urban anti-drone, and create an industry-leading intelligent anti-drone solution.