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Open nowPosted 78 days ago

【27 届实习】感知算法实习生

qcraft/campus31 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now【27 届实习】感知算法实习生qcraft/campus · Beijing, Chinese Mainland

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Early applications get read.

11.5% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.0%1 day
  2. 4.3%3 days
  3. 11.5%7 days
  4. 18.1%14 days
  5. 35.6%30 days
  6. 44.6%60 days
This job: posted 78 days ago

The posting

实习期间将会涉及以下部分方向 BEV OCC 感知前沿探索：探索车道线检测、实时局部建图方案等前沿技术，推动视觉感知在自动驾驶场景中的研发落地。 多传感器感知融合：参与相机、激光雷达、毫米波雷达等多传感器数据融合算法的设计与开发，研究 BEV 空间下的前融合 / 中融合 / 后融合方案，提升复杂场景下的感知精度与鲁棒性。 主动安全感知：面向 AEB（自动紧急制动）、FCW（前向碰撞预警）、LDW（车道偏离预警）、BSD（盲区检测）等主动安全功能，参与安全关键场景下的感知算法开发，包括动目标检测、Cut-in 识别、行人 / 弱势交通参与者保护等。 时序融合与目标跟踪：参与多帧时序融合与多目标跟踪算法的研发，优化目标状态估计与轨迹预测的准确性，保障高速行驶场景下的感知时延与可靠性。 全栈工程能力培养：从数据采集分析、模型算法设计到部署验证的全链路实践，培养端到端 AI 工程师能力。 系统理解与工程实践：了解自动驾驶系统架构设计和技术细节，参与感知模块与规划 / 控制模块的协同联调。

职位要求 优秀的在校硕士或博士毕业生，包含但不限于计算机、模式识别、人工智能、自动化、电子工程、软件工程等相关专业，27届优先、公司提供转正机会。 掌握 C/C++ 或 Python 编程语言之一，掌握基础数据结构和算法。 掌握深度学习基础知识，熟悉目标检测 / 分割 / 分类等常用算法，熟练使用 PyTorch 框架。

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