软件工程师，基于机器学习的控制
Software Engineer, ML-based Controls
你将
设计并开发以数据驱动和机器学习方法解决车辆控制问题，将现代机器学习应用于传统上使用经典方法解决的领域。
开发车辆行为和动态的模型，并将其集成到闭环仿真中。
应用机器学习来提升控制器在不同车辆和运行条件下的适应能力。
作为一支跨学科工程师和研究科学家团队的一员，采用AI优先的方法实现大规模安全自动驾驶。
从概念化和离线实验到仿真和车辆验证，全程负责问题的解决。
构建数据管道、评估指标和工具，以衡量学习方法是否优于传统基准。
参与技术与架构讨论，分享想法，帮助定义学习与经典控制在安全关键系统中的共存方式。
资格要求：
硕士/博士或学士学位，且在机器人、控制、机械/电气工程、计算机科学和/或其他相关技术领域有至少4年行业经验。
在控制理论和动态系统方面有深入理解（例如，MPC、最优控制、状态估计、系统识别、运动学和动力学车辆建模）。
有将机器学习应用于物理系统的实际经验，包括硬件在环而非仅仿真。
具备Python和C++的生产级编码技能，以及使用PyTorch等深度学习框架的经验。
具备使用线性代数、优化、统计与概率解决问题的扎实能力。
能够快速原型化和测试新算法，并设计实验验证其有效性。
开放思维，善于协作，乐于助人。
对自动驾驶技术充满热情，喜欢解决难题并创造创新解决方案。
该职位的美国年薪范围为：241,000 - 320,000美元美元，另加具有竞争力的福利和待遇。Waabi US Inc. 的年薪范围根据公司薪酬政策，结合多种因素确定。注意：公司会为该职位员工提供额外补偿，包括股权激励和年度绩效奖金。
查看英文原文
You Will…
Design and develop data-driven and machine-learned approaches to vehicle control problems, bringing modern ML to a domain traditionally solved with classical methods.
Develop learned models of vehicle behavior and dynamics, and integrate them into the closed-loop simulation.
Apply machine learning to improve how the controller adapts across vehicles and operating conditions.
Be part of a team of multidisciplinary Engineers and Research Scientists using an AI-first approach to enable safe self-driving at scale.
Own problems end to end, from conceptualization and offline experimentation through simulation and on-vehicle validation.
Build the data pipelines, evaluation metrics, and tooling needed to measure whether a learned approach outperforms the classical baseline.
Participate and share ideas in technical and architecture discussions, helping define how learning and classical control coexist in a safety-critical stack.
Qualifications:
MS/PhD or Bachelors degree with a minimum of 4 years of industry experience in Robotics, Controls, Mechanical/Electrical Engineering, Computer Science and/or similar technical field(s) of study.
Demonstrated depth in control theory and dynamic systems (e.g., MPC, optimal control, state estimation, system identification, kinematic and dynamic vehicle modeling).
Hands-on experience applying machine learning to a physical system, with real hardware in the loop rather than simulation alone.
Production-quality coding skill in Python and C++, and experience with deep learning frameworks such as PyTorch.
Solid problem solving skills using linear algebra, optimization, statistics & probability.
Ability to rapidly prototype and test new algorithms, and to design the experiments that prove whether they work.
Open-minded and collaborative team player with the willingness to help others.
Passionate about self-driving technologies, solving hard problems, and creating innovative solutions.
The US yearly salary range for this role is: $241,000 - $320,000 USD in addition to competitive perks & benefits. Waabi US Inc.’s yearly salary ranges are determined based on several factors in accordance with the Company’s compensation practices. Note: The Company provides additional compensation for employees in this role, including equity incentive awards and an annual performance bonus.