Data Infrastructure Engineer
TLDR
Design, build, and maintain petabyte-scale data pipelines and infrastructure for robotics foundation model training, unifying real-world teleoperation and synthetic data to advance Physical AI.
What You’ll Do
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
What You’ll Bring
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)
Bonus: Experience supporting AI systems, in particular embodied AI like self-driving
Genesis builds general-purpose robots designed to tackle a wide range of physical labor tasks, empowering people to focus on creativity and exploration. Catering to industries seeking advanced automation solutions, our flagship creation, Eno, is leading the way in real-world applications. With a unique blend of American and French innovation, we harness cutting-edge technology to redefine work and productivity.