Responsibilities
As a key technology leader within the team, you will:
1. Define the overarching data AI technology blueprint to support humanoid robot perception, decision-making, control.
2. Design implement scalable, high-availability data architectures fAI model training in robotics, materials, component development.
3. Build maintain robust data pipelines fthe collection, storage, processing, provisioning of large-scale, complex datasets.
4. Ensure data quality, governance, compliance throughout the entire data lifecycle.
5. Provide expert guidance on AI model development deployment across project teams.
6. Serve as a subject matter expert in data-driven methodologies AI architecture.
7. Collaborate with motion control application specialists to integrate sensory control data fAI training deployment.
8. Develop maintain infrastructure ffoundation models (e.g., LLMs, VLMs, VLAs) to enable robotic perception, reasoning, action planning.
9. Build scalable pipelines ftraining fine-tuning large models using both real-world simulated data.
10. Integrate multimodal models (vision-language-action) robotic systems to enable adaptive task execution.
11. Contribute to the development of simulation-to-real pipelines fhumanoid robotics.
Qualifications
1. Master’s degree higher in Computer Science, Data Engineering, Data Science, a related field, 10+ years of experience in industry academia.
2. Proven expertise in designing data architecture developing data pipelines (batch streaming).
3. Proficiency with cloud on-premises data platforms (e.g., AWS, Azure, Hadoop, Spark).
4. Strong programming skills in Python hands-on experience with machine learning frameworks.
5. Practical experience with foundation models (e.g., LLMs, VLMs, VLAs) large-scale AI systems.
6. Solid understanding of data management best practices.
7. Excellent communication skills in English.
Nice-to-Haves:
- Experience with AI/ML techniques such as Reinforcement Learning Deep Learning.
- Familiarity with robotics data (e.g., sensdata, simulation, telemetry).
- Experience in motion data processing control signal modeling.
- Background in training, fine-tuning, integrating foundation models frobotic applications.
- Knowledge of data governance security standards.
- Understanding of digital twin workflows control-policy optimization.
更新于 2025-12-27