Algorithm Application Scientist - Large Model Applications

Team Introduction: We are the Engineering Architecture team of the PICO-Interactive Perception R&D Department. We are responsible for the architecture design and engineering implementation in the Interactive Perception Department. We focus on exploring the low-power consumption deployment of AI models, strive for excellence and aim to become an international team with leading technology. We are looking for talented individuals to join our team in 2027. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Launch your career where inspiration is infinite at our Company. Successful candidates must be able to commit to an onboarding date by end of year 2027. Please state your availability and graduation date clearly in your resume. Topic Content: The rapid advancement of AI Agents is set to have a far-reaching and transformative impact on daily life. As the hardware bridge linking AI Agents to the physical world and end users, intelligent hardware acts as a vital gateway for agents to perceive their environment and recognize user intent. Enabling AI Agents to maintain round‑the‑clock environmental awareness and efficiently capture real‑time user intentions is essential to improving their everyday service experience. This topic seeks to overcome the limitations of conventional visual perception systems. By deeply integrating sensing and computing, it explores full‑stack innovation spanning from low‑level hardware to high‑level algorithms. Key efforts include developing next‑generation sensors with real‑time understanding capabilities, investigating non‑traditional visual capture and compression techniques, and designing novel hardware architectures to run advanced algorithms—enabling highly efficient coordination across sensing, processing, and communication. Topic Challenge: Break free from the framework of conventional sensing systems, explore novel sensors, signal processing and compression schemes to achieve highly energy-efficient sensing tasks, while enabling seamless integration with large models. Topic Value: Breakthroughs in this research direction will enable intelligent hardware to better connect AI, users, and daily life. Against the backdrop of the AI Agent era, this will unlock the gateway to the next generation of intelligent hardware terminals and open up broader technological possibilities. Job Responsibilities - technical solution design, model selection, fine-tuning (SFT), RAG (Retrieval-Augmented Generation) implementation, and application deployment. You will play a key role in promoting the in-depth integration of large model technology with real-world business scenarios. - Keep abreast of the latest technological trends in global large models (e.g., GPT, Gemini, LLaMA series), conduct in-depth technical research and verification, and apply cutting-edge technologies to project practice to continuously enhance application performance and user experience. - Collaborate closely with algorithm, product, and business teams to deeply identify industry pain points, translate business requirements into actionable technical solutions, and drive the iterative upgrading of large model applications. - Participate in the design and optimization of large model application workflows, leverage Agent and tool calling technologies to expand scenario coverage and improve automation levels, and explore innovative applications of large models in vertical sectors. - Undertake the collation of technical documents, project summary, and experience accumulation, and contribute to the construction and improvement of the team’s technical knowledge system. Minimum Qualifications - Individuals who are completing or recently completed a PhD in Software Development, Computer Science, Computer Engineering, or a related technical discipline. Top academic performance during school is highly preferred. - Technical Foundation: Possess a profound understanding of the fundamental principles of large models and deep learning, be familiar with common deep learning frameworks (e.g., TensorFlow, PyTorch), and be proficient in at least one programming language (Python is preferred). - Learning Ability: Demonstrate strong self-learning ability and adaptability, with the capability to quickly master new technologies and tools in the large model field and independently solve complex technical problems. - Communication & Collaboration: Strong communication skills in English and Mandarin (this role partners closely with teams and stakeholders based in China) Have excellent logical thinking and cross-team communication skills, able to clearly articulate technical ideas and collaborate efficiently with team members to advance project progress. - Passion & Attitude: Be full of passion for large model technology and its applications, with a proactive work attitude, a strong sense of responsibility, and a pioneering spirit of innovation. Preferred Qualifications - Relevant Project Experience: Experience in large model-related projects, including but not limited to large model fine-tuning, prompt engineering, RAG system development, and Agent application development. Academic assignments, research projects, and internships are all recognized. - Academic Achievements: Published academic papers in fields related to large models and deep learning, obtained relevant patents, or won awards in technical competitions (e.g., Kaggle, AI-related competitions). - Familiarity with common large model application tools and frameworks (e.g., LangChain, LlamaIndex), with experience in the integration and optimization of vector databases (e.g., Elasticsearch). - Understanding of large model application scenarios in XR fields , with relevant scenario-oriented thinking and practical experience.