解决方案-北美

What You'll Do

-Deep Dive into Frontier Algorithms: As our core technical representative on the customer side, you will embed deeply into the R&D processes of our clients’ embodied intelligence teams (VLA, world models, etc.). You will work directly with algorithm scientists and model training leads to precisely understand their data requirements as models evolve.

-Cutting-Edge Data Solution Design: Take ownership of designing comprehensive solutions for the complex multimodal data (vision, language, proprioception, force/torque, etc.) and temporal requirements of embodied intelligence-covering full-scene teleoperation and embodiment-free data collection, end-to-end data annotation, simulation-generated synthetic data, and data-alignment pipelines.

-Data Evaluation & Feedback Loop: Design and refine data quality evaluation frameworks aligned with embodied intelligence algorithm metrics. Through failure analysis, you’ll drive iterative improvements to data collection specifications and annotation rules—helping our clients accelerate model capability growth.

End-to-End Project Delivery: As the technical owner on the front end, you will orchestrate internal data collection teams, annotation pipelines, and engineering teams to deliver high-quality, customized data solutions from start to finish, ensuring successful project delivery.

-Industry Knowledge & Product Leadership: Stay ahead of industry trends and distill insights from serving top-tier clients into company-level embodied data product standards, driving the evolution of our internal data toolchain (e.g., multimodal alignment tools and 4D annotation platforms).

What We're Looking For

-Educational Background: Master’s degree or above in Computer Science, Artificial Intelligence, Robotics, Automation, or a related field.

-Algorithm & Data Expertise (Core):Deep understanding of frontier embodied intelligence algorithm paradigms (e.g., Vision-Language-Action models, World Models, Imitation Learning, Reinforcement Learning).

-Clear grasp of the specific data formats, distributions, alignment precision, and long-tail scenario requirements these algorithms demand during training.

-Professional Experience: 3+ years of experience in AI data solutions, technical architecture, or algorithm/data engineering.

-Candidates with the following backgrounds are highly preferred:

- Autonomous Driving: Familiarity with end-to-end AD data closed loops, 4D annotation, and simulation data.

- LLM / Multimodal Foundation Models: Experience with RLHF, SFT data construction, and complex multimodal alignment.

- Robotics: Hands-on experience in robotics R&D or data processing.

-Soft Skills: Exceptional technical translation and communication abilities—you can bridge the gap between complex algorithmic language and actionable engineering SOPs. Strong resilience under pressure and proven project coordination skills.