特斯拉嵌入式软件工程师, 能源产品 Embedded Software Engineer, Energy Product
任职要求
· BS or higher in Engineering, Computer Science, Physics or proof of exceptional skills in related fields, with practical engineering experience.
· Experience shipping code, receiving feedback and being relentless ensuring customer experience is positive. Experience documenting firmware design and authoring specifications.
· Shows a keen understanding of physics and follows first principles in design and development. Familiar with electrical test tools like scopes, network analyzers, power supplies, loads.
· Excellent communication skills, say something when you don’t know, be available to other team members when questions arise.
· At least one of the following: capable of delivering top quality C code in a real time embedded environment, experience writing Python scripts.
· Remain engaged, proactive and positive in tough circumstances/challenging problems.
· Own assignments and take accountability for overall team success.
· Ability to collaborate and communicate complex technical concepts.
Nice to Have:
· Interest in factory analytics and metrics: first-pass yield, cycle time, test coverage, failure modes.
· Knowledge of basic theory of operations for battery charging systems.
· Experience with Ethernet, high speed com…工作职责
Role: Tesla Energy is looking for a motivated Firmware Integration Engineer to bring the next generation of Residential and Industrial charging products to the market. As a member of the Firmware Integration team, you will be responsible for delivering high quality firmware, software, and hardware to the manufacturing line. You will architect the software solutions for manufacturing quality Energy products (e.g. Powerwall, Megapack) in our factories. Rethink manufacturing processes and test equipment dependency with our in-house product and design teams. Engineer a software stack capable of ultra-high volume production capacity across our entire supply chain. Ensure flexibility within our product design and manufacturing test functionality to achieve critical business objectives. You will have the opportunity to solve challenging problems on the production line and in the field. Collaborate closely with hardware, manufacturing, and service engineering to design firmware and automation solutions for a seamless commissioning experience. You will show outstanding organizational and communication skills and an eagerness to learn in an ever-evolving environment. Manage your projects with a positive attitude and be a team player in a collaborative work environment. Responsibilities: · Develop, enhance and debug new and existing software in C, Python, or Golang. · Perform hardware and firmware integration of current and next generation Tesla charging systems. · Author product test specification of home and commercial charging products for optimal coverage at each step in the assembly process. · Design robust and exhaustive test procedures for high voltage power electronics, battery modules, thermal systems, and solar product assemblies. · Contribute to software architecture design, development of software applications, and integration into manufacturing processes and production lines. · Track and communicate project status and risks to the wider organization. Interact with engineers from multiple teams. · Hands-on with hardware bring up, debug issues and devise solution paths. · Provide technical and leadership excellence for the team. You will make critical decisions and lead from the front with support from experienced engineers. · The position duties may require travel to Tesla and/or supplier factories.
AI搜索和智能体产品后端系统研发: 1. 设计并实现AI搜索Agent应用,包括Query理解、记忆存储、环境感知等模块的集成与优化。 2. 负责Agentic Search(搜索智能体)技术探索和架构研发,支持多模态(文本、图像、视频)检索与应用创新。 3. 抽象并开发企业级别的AI应用平台,支持Agent相关应用的接入与扩展,确保平台的高可用性和可扩展性。 4. 实现平台的模块化设计,支持快速迭代与功能扩展,满足AI时代本地生活服务领域智能体应用快速发展需求。 5. 与业务部门(如产品、运营团队)协作,将AI搜索能力嵌入现有工作流(如智能问答、个性化推荐)。 6. 负责AI系统的日常运维,包括异常监控、接口优化及用户培训,确保生产环境高效运行。
1、嵌入式AI系统开发: • 负责RTOS系统平台上多模态AI终端产品的研发,包括方案评估、软件架构设计、核心功能模块(如人脸/手势识别、行为分析)开发与部署; • 主导端侧AI模型轻量化、跨平台推理框架适配(TensorFlow Lite/MNN/NCNN)及NPU芯片的性能优化(如内存、功耗、实时性); • 结合硬件特性设计轻量化模型架构,完成从算法训练到嵌入式端侧部署的全链路开发。 2、多模态算法工程化: • 优化计算机视觉算法在嵌入式设备(IoT/AR硬件/AI机器人)的落地效果,解决低算力、高延迟、多干扰场景下的工程挑战; • 开发芯片算子库适配方案,参与芯片选型、AI工具链优化及端云协同架构设计; • 探索多模态交互(视觉+语音+传感器)在智能终端的创新应用,如AI玩偶、陪伴机器人等。 3、跨团队协作与交付: • 与芯片厂商、算法团队、硬件团队协同开发,主导端侧SDK集成及性能调优,确保产品按时交付; • 支持产品量产落地,保障系统稳定性与用户体验。