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About the Role
Design, build, and maintain large-scale data pipelines for robotics foundation model training and evaluation at petabyte scale. Own core data infrastructure including data models, storage systems, ingestion pipelines, transformation frameworks, and orchestration layers. Standardize data models and unify processing pipelines across real-world teleoperation and synthetic simulation datasets. Collaborate with a team committed to building general-purpose Physical AI.
Responsibilities
- Design, build, and maintain large-scale data pipelines (batch and streaming) for robotics foundation model training and evaluation at petabyte scale
- Own core data infrastructure: data model, storage systems, ingestion pipelines, transformation frameworks, and orchestration layers
- Standardize data models and unify processing pipelines across real-world teleoperation and synthetic simulation datasets
- Collaborate with a team of driven individuals committed to building general-purpose Physical AI
Requirements
- Excellent software engineering skills (Python, Go, or similar)
- Extensive experience designing, building, and maintaining large-scale data pipelines (8+ years)
- Deep understanding of distributed systems (Spark, Kafka, or similar)
- Extensive experience with data storage technologies (data lakes, warehouses, object stores like S3)
- Experience running and maintaining production-grade infrastructure (Kubernetes, Terraform)
- Experience supporting AI systems, in particular embodied AI like self-driving
Skills
- Python
- Go
- Spark
- Kafka
- Data lakes
- Data warehouses
- Object stores
- S3
- Kubernetes
- Terraform
- AI systems
- Embodied AI
- Self-driving
Experience Level
- 8+ years