小鹏汽车Research Scientist (Multimodal)

· Lead strategic analysis on global trends in Physical AI, including autonomous driving, embodied intelligence, robotics, and sensorimotor foundation models. · Continuously monitor and benchmark key players (e.g., Tesla FSD, Waymo Robotaxi) and emerging technologies in North America and globally. · Conduct exploratory research on cutting-edge technologies related to world models, multimodal large models, and planning frameworks in AI. · Produce high-quality technical and strategic insight reports for internal stakeholders to inform roadmap and business decisions. · Collaborate with R&D and product teams to shape future research directions and support decision-making with clear, data-driven foresight. · Participate in academic engagements, including paper drafting and submission to top-tier AI conferences (e.g., NeurIPS, CVPR, ICRA, RSS).

• Research, design, and prototype methods to leverage LLMs for product scenarios such as text understanding, summarization, dialogue, translation, content generation, and reasoning. • Fine-tune, adapt, and optimize pre-trained LLMs for domain-specific tasks while balancing model performance, efficiency, and cost. • Develop scalable pipelines for data collection, cleaning, augmentation, and evaluation. • Collaborate with product and engineering teams to translate applied research into production-quality features. • Define and track key performance metrics for LLM-based features, including accuracy, latency, robustness, and user satisfaction. • Stay current with advances in generative AI, multimodal models, and applied ML techniques, and bring forward innovative ideas to improve our products. • Publish technical insights internally (and externally where appropriate) to advance organizational knowledge and thought leadership.

• Ship features with PM & Engineering. Co‑own scenario goals; translate product requirements into scientific plans and productionized solutions that meet quality/latency/cost targets. • Model development & optimization. Design, fine‑tune, and evaluate models for LLM‑based authoring, summarization, reasoning, voice/chat, and personalization (e.g., SFT, alignment, prompt/tool use, safety filtering, multilingual & multimodal). • Data & evaluation at scale. Build/extend data pipelines for curation/labeling/feature stores; author offline eval harnesses; run online A/Bs and interleavings; define guardrails and success metrics; author scorecards and decision memos. • Production ML engineering. contribute to service code and configs; add monitoring, tracing, dashboards, and auto‑scaling; participate in on‑call and postmortems to improve live‑site reliability. • Responsible AI. Produce review artifacts, document mitigations for safety/privacy/fairness, support red‑teaming and sensitive‑use checks, and align with Microsoft’s Responsible AI Standard. • Collaboration & mentoring. Partner across PM/ENG/Design/CE/ORA/CELA; share methods and code, review PRs, improve reproducibility and documentation; mentor junior scientists.

• Ship features with PM & Engineering. Co‑own scenario goals; translate product requirements into scientific plans and productionized solutions that meet quality/latency/cost targets. • Model development & optimization. Design, fine‑tune, and evaluate models for LLM‑based authoring, summarization, reasoning, voice/chat, and personalization (e.g., SFT, alignment, prompt/tool use, safety filtering, multilingual & multimodal). • Data & evaluation at scale. Build/extend data pipelines for curation/labeling/feature stores; author offline eval harnesses; run online A/Bs and interleavings; define guardrails and success metrics; author scorecards and decision memos. • Production ML engineering. contribute to service code and configs; add monitoring, tracing, dashboards, and auto‑scaling; participate in on‑call and postmortems to improve live‑site reliability. • Responsible AI. Produce review artifacts, document mitigations for safety/privacy/fairness, support red‑teaming and sensitive‑use checks, and align with Microsoft’s Responsible AI Standard. • Collaboration & mentoring. Partner across PM/ENG/Design/CE/ORA/CELA; share methods and code, review PRs, improve reproducibility and documentation; mentor junior scientists.