
文远知行机器学习工程师(预测)
任职要求
PhD in Electrical Engineering, Computer Science/Engineering or a related field.
3 or more years of relevant work or lab experience in Machine Learning, Deep Learning or High-Performance Computing
Excellent knowledge of theory and practice of machine learning.
Excellent programming skills in some rapid prototyping environment such as MATLAB …工作职责
WeRide is a smart mobility start-up whose mission is to transform mobility with autonomous driving. We are committed to build better transportation experience that’s safe, efficient, affordable and joyful. We have an elite team of entrepreneurs and technologists who share the same passion and pursue continuous excellence in their work. WeRide.ai is looking for a machine learning engineer for the prediction team. In this impactful role, you will collaborate with a best-in-class team of engineers to tackle hard problems and help advance mobility solutions to improve everyday lives. You will be responsible in such fields: Active learning and Bayesian optimization Anomaly detection Deep networks Distributed/parallel learning algorithms Learning control Predictive modeling
1、负责大数据特征挖掘、数据建模,挖掘大数据价值并应用到物流供应链相关的预测业务场景中; 2、利用数据挖掘和机器学习建模技术,进行模型开发与部署应用; 3、负责海量数据分析、特征挖掘、算法选型迭代,就业务指标评估、解决方案和预测效果进行持续的分析和改进; 4、基于业务对接产品、研发团队,参与方案评估、策略分析和数学建模,开拓前沿建模技术并结合业务场景解决实际痛点。
1. 核心算法研发与创新 * 基于公司内外部海量的供应链数据(仓储、物流、销售等),进行深度机器学习与深度学习建模。 * 核心聚焦时序预测领域的创新与研究,涵盖商品需求预测、库存水位预测、运输时效预估等关键场景。 * 探索AI智能体在自动化补货决策等领域的应用。 2. 全链路模型交付 * 独立负责从数据到业务价值的模型全链路工作,包括:业务问题定义、数据清洗、特征工程、模型训练与调优、在线/离线部署、A/B测试、效果监控与评估,确保模型稳定产生业务价值。 3. 业务赋能与洞察 * 深入理解供应链业务逻辑,与采购、计划、仓储等团队紧密协作,将复杂业务问题转化为可量化的算法问题。 * 通过数据分析和模型可解释性工具,为业务决策提供深度洞察与建议。 4. 技术前瞻与沉淀 * 跟踪时序预测、深度学习、多智能体系统等前沿技术,推动其在业务中的可行性验证与落地。 * 沉淀可复用的算法组件、工具与方法论,提升团队整体效率。

如果base深圳,前面半年需要来广州出差培训学习; 岗位主要负责对障碍物未来可能的行为和运动轨迹进行预测,并给出概率和不确定性估计,为下游的决策规划提供依据; 您将负责的领域包括: 主动学习与贝叶斯优化 异常检测 深度神经网络 分布式/并行学习算法 学习控制 行为/轨迹预测建模