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发布于 2026-11-11 英文原文

资深工程师(物理AI - 系统工程)

Staff Engineer Physical AI Systems

ルネサス エレクトロニクス

职种工程 雇用形态—
工作地点Ottawa, ca 薪资面议

职位概要

该职位隶属于工程创新办公室的探路工作室,负责开发与验证面向人形及工业机器人的物理AI系统模型与数据流技术。工作内容包括:将需求转化为硬件、机械、计算与软件设计选择;设计、原型制作、集成并验证人形硬件与机械子系统(如关节手与手臂、执行器与传感器集成、机电接口);开发并评估基于学习的感知、规划、控制与操作流程(含基础模型、视觉-语言-动作模型、模仿学习与强化学习);开发维护实验室虚拟系统模型及机器人软硬件基础设施;评估并原型化神经形态及超低功耗计算方案并集成到系统演示中;建立可复现仿真、数据采集、训练与评估的最佳实践,分析复杂故障模式并验证仿真到现实的迁移。应聘资格:硕士学历加6年相关研究工程经验,或博士学历加3年经验;扎实的数学、物理与机器人学基础(运动学、动力学、感知、规划、控制、抓取、操作、接触丰富交互);具有NVIDIA Isaac Sim、MuJoCo或类似物理仿真平台及硬件验证经验;具备机械CAD与电子子系统及PCB设计经验;熟悉基于学习的机器人方法;具备仿真与真实数据采集、可复现评估及仿真到现实工作流经验;精通Python与C/C++;具有机电集成、执行器与传感器选型建模经验;了解神经形态与内存计算者优先;能分析功耗、延迟、计算资源、热行为与任务性能的系统级权衡;有算法硬件实现及与电子、系统架构、RTL设计与验证团队协作经验,数字ASIC设计验证经验为加分项;在知名机器人会议期刊发表论文。学历:机器人、机械工程、电气工程、计算机工程、计算机科学或密切相关领域硕士(博士优先)。Renesas为嵌入式半导体解决方案提供商,全球超21000名工程师,遍布30多国,文化为TAGIE(透明、敏捷、全球、创新、创业),提供有竞争力的薪酬福利。需符合美国出口管制法规要求。

职位描述

Job Description We are seeking a Staff Engineer (Physical AI - System Engineering) to join the Pathfinding Studio within the Engineering Innovation Office. In this role, you will develop and validate technologies related to Physical AI systems models and dataflow for humanoid and industrial robotics. The role combines hands-on design, virtual and hybrid system modeling, algorithm–hardware co-design, experimental validation, and cross-disciplinary collaboration to achieve project milestones. Responsibilities: · Contribute to Physical AI related technology development for humanoid and industrial robotics, translating requirements into hardware, mechanical, compute, and software design choices. · Design, prototype, integrate, and validate humanoid hardware and mechanical subsystems, including articulated hands and arms, actuator and sensor integration, and electromechanical interfaces. · Develop and evaluate learning-based perception, planning, control, and manipulation workflows, including foundation models, vision-language-action models, imitation learning, and reinforcement learning as appropriate to project objectives. · Develop and maintain virtual system models and robotics hardware and software infrastructure for the lab environment. · Evaluate and prototype neuromorphic and similar ultra-low-power computing approaches for humanoid sensing, perception, and control; integrate candidate computing platforms into system demonstrations. · Develop and apply best practices for reproducible simulation, data collection, training, and evaluation; investigate complex failure modes through in-depth analysis of variable factors and validate sim-to-real transfer against system requirements. Qualifications · Six years of related research and engineering experience with a Master’s degree, or three years with a PhD. · Strong foundation in mathematics, physics, and robotics, including kinematics, dynamics, perception, planning, control, grasping, manipulation, and contact-rich interaction. · Hands-on experience with NVIDIA Isaac Sim, MuJoCo, or comparable physics-based simulation and virtual system modeling platforms, including validation against physical hardware. · Hands-on experience with mechanical CAD and electronic subsystem and PCB design and tools targeting robotics. · Experience with learning-based robotics methods, such as foundation model adaptation, vision-language-action models, imitation learning, reinforcement learning, or generative and world models. · Experience with simulation and real-world data collection, data quality, reproducible evaluation, and sim-to-real workflows; strong Python and C/C++ development skills in embedded, and distributed CPU-, or GPU-based environments. · Experience with electromechanical integration, actuator and sensor selection and sensor modeling, and evaluation of mechanical constraints for articulated hands, arms, or other humanoid mechanisms. · Knowledge in Neuromorphic and in-memory computing and modeling considered an advantage. · Ability to measure and analyze system-level trade-offs in power and energy consumption, latency, compute resources, thermal behavior, and task performance. · Experience translating algorithms into hardware implementations and collaborating with electronics, system architecture, RTL design, and verification teams; digital ASIC design and verification experience is an asset. · Publications in reputed conference and journals related to robotics. Education: Master’s degree (PhD preferred) in Robotics, Mechanical Engineering, Electrical Engineering, Computer Engineering, Computer Science or a closely related field. Additional Information Renesas is an embedded semiconductor solution provider driven by its Purpose, To Make Our Lives Easier . With a global team of over 21,000 engineers and problem solvers in more than 30 countries, we offer the opportunity to work on world‑leading technology for Automotive, Industrial, Infrastructure, and IoT, shaping a safer, healthier, greener, and smarter future. At Renesas, TAGIE is our culture, grounded in being Transparent, Agile, Global, Innovative, and Entrepreneurial. It shapes how we work, grow and deliver on our purpose together. This collaborative spirit and mindset drive our semiconductor technology to transform industries and impact millions of lives. We believe in rewarding our employees with a competitive benefits package alongside their salary. More information will be provided during the hiring process. Are you ready to join our team and shape the future with us? Export Control Compliance Condition Renesas Canada must at all times comply with U.S. and Canadian export control legislative requirements. Current U.S. export control laws require that Renesas Canada obtain a U.S. government export license prior to employing persons in positions with access to certain technology. All positions at Renesas Canada have direct or indirect access to this technology. As a result, it is necessary for Renesas Canada to determine if it would need an export license for new employees. To do so, we ask all candidates for employment whether their most recent country of citizenship or permanent residence is one of the countries specified in the export controls laws or regulations. Renesas recognizes that you are entitled to human rights and privacy protections in the workplace and takes these obligations seriously. As such, we want you to know that your decision to complete the export control questions is entirely voluntary. Regrettably, should you choose not to complete these questions, we cannot consider you for employment because doing so would jeopardize our ability to comply with the applicable export controls laws. Should you choose to complete the questions, we will use the information collected only to determine if we would need an export license to employ you and not for any other purpose. Successful candidates must be eligible to meet the requirements of U.S. export control regulations, including (if applicable) the issuance of any required export license prior to starting employment at Renesas Canada. The decision whether to or not to file or pursue an export license application is at the sole discretion of Renesas Canada.