安克创新Assistant Algorithm Engineer

需要英文简历 1. Participate in technical support and solution design for the company's core products, including computer vision, AI agents, and Intelligent robot, assisting in customer requirement investigation, feature definition, and iteration planning for AI scenarios. 2. Engage in end-to-end management of AI projects, including project planning, resource coordination, progress tracking, and risk identification, helping to ensure high-quality project delivery. 3. Assist in customer interactions, participate in business pain point analysis, and collaborate on designing technically feasible and user-friendly AI solutions while helping to maintain customer relationships. 4. Collaborate with algorithms, software development, and business teams to promote product feature implementation and project delivery, enhancing cross-team efficiency. 5. Stay updated on cutting-edge AI technologies and trends, incorporating user feedback and business data to contribute to product optimization and innovation. 1. 参与公司AI视觉、AI Agent及智能机器人等核心产品的技术支持与解决方案设计，协助完成AI场景的需求调研、功能定义及迭代规划； 2. 参与AI类项目的全流程管理，包括项目计划制定、资源协调、进度跟踪与风险识别，协助推动项目高质量交付； 3. 协助与业务对接，参与痛点分析，共同制定技术可行、体验优秀的AI解决方案，并协助维护与业务方的关系； 4. 与算法、软件开发及业务团队协同工作，推动产品功能落地与项目交付，提升多团队协作效率； 5. 跟踪AI前沿技术与发展趋势，结合用户反馈与业务数据，参与产品优化与创新迭代。

About the Role
TCL Industries seeks a visionary Embodied AI Architect to lead software architecture for next-generation home assistant robots. You will design intelligent, interactive systems, integrating perception, planning, navigation, manipulation, HRI, and emotional modules. Collaborate with multidisciplinary teams to drive robotics innovation. Key Responsibilities •System Architecture: •Design and oversee end-to-end software architecture for embodied AI in home robots. •Define interfaces and protocols for system components. •Manage sensor and camera data for informed AI decision-making. •Guide middleware, simulation, and tool selection. •Integration & Optimization: •Ensure seamless integration across hardware, AI algorithms, and cloud services. •Profile, debug, and optimize system performance. •Establish best practices for development, testing, and deployment. •Collaboration: •Work with hardware, data science, and product teams to align technical and product goals. •Cooperate with researchers to design and develop advanced algorithms for perception, reasoning, planning, human-robot interaction (HRI) and emotional intelligence •Strategic Input: •Contribute to long-term vision and planning. •Represent the lab at conferences and industry events.

Why Join Us We're seeking an AI Algorithm Engineer who will lead the design and implementation of cutting-edge conversational systems for TCL products such as TV, mobile phones, smart glasses and home robots. This position is ideal for someone who is motivated to innovate, tackle challenging problems, and collaborate effectively in cross-functional teams. Key Responsibilities Lead the algorithm design and data flow architecture for specific scenarios. Adapt LLMs to specific application scenarios via continued pre-training or fine-tuning. Evaluate and monitor model performance using both quantitative and qualitative metrics; recommend the best models for specific tasks. Stay current with AIGC trends and apply cutting-edge technologies and methods to work. Solve complex problems, share knowledge, and collaborate across departments.

The Role TESLA is offering a full-time IT Support DevOps AI position in the Information Technology Department (Work Location: Tesla Giga Factory Shanghai). If you are a versatile expert integrating AI development, DevOps practices—someone who can efficiently tackle challenges, solve complex technical problems in user support and experience scenarios, and reject repetitive and inefficient work patterns—this role is perfect for you. IT Support DevOps AI is a core role connecting the company’s IT systems and user-facing processes, standing at the forefront of enhanced user support implementation. You will engage in work across multiple domains, including AI technology R&D, containerized deployment, and operational support. Through technical practice, you will support the company in optimizing user interactions, improving support efficiency, and contributing to the core goal of user experience transformation. Responsibilities • Undertake AI algorithm R&D, model optimization, and training, with a strong emphasis on fine-tuning (FT), supervised fine-tuning (SFT), reinforcement learning (RL), and advanced tuning techniques; focus on user support scenarios such as data analysis, query resolution, issue detection, and automated assistance to ensure AI technology aligns with user experience needs. • Complete the deployment, monitoring, and scaling of AI solutions based on container technologies like Kubernetes (K8s) and Docker, ensuring high availability and stability of the system in the operational environment, while integrating AI underlying technologies like neural networks and Transformer architectures for efficient performance. • Participate in DevOps process development, optimize the full lifecycle of AI model and system development, testing, and deployment, and realize automated deployment, continuous integration (CI), and continuous delivery (CD), incorporating RL-based optimization and model tuning for adaptive user support systems. • Collaborate with user support-related departments such as helpdesk, customer service, and product teams to deeply understand user pain points and provide data-driven AI technical solutions, leveraging SFT and attention mechanisms to enhance personalized user experiences. • Respond quickly to technical requirements and faults in user-facing systems, troubleshoot issues in AI systems, container clusters, and network environments, minimize impacts on user interactions, and improve support efficiency and satisfaction through advanced AI tuning and underlying model diagnostics. • Track cutting-edge technologies in the AI and DevOps fields (e.g., large language models with FT/SFT/RL integration, cloud-native operations) and industry trends, promote the pre-research and application of new technologies in user support scenarios, and continuously optimize system performance using techniques like model compression and quantization.