Data Infrastructure

Genesis AI; San Carlos (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

Genesis AI in California is seeking a senior data engineering lead to design, build, and maintain large-scale data pipelines for robotics foundation model training and evaluation at petabyte scale. You will own core data infrastructure, including data models, storage, ingestion, transformation, and orchestration layers.

You will standardize data models, unify processing across real-world teleoperation and synthetic simulation datasets, and collaborate with a team focused on building

Qualifications

• 8+ years of experience building data pipelines and data infrastructures.
• Proficiency in Python or Go and production-grade software engineering practices.
• Deep understanding of distributed systems and data storage technologies.

Responsibilities

• Design, build, and maintain large-scale data pipelines for robotics foundation model training and evaluation.
• Own core data infrastructure: models, storage, ingestion, transformation, and orchestration.
• Standardize data models and unify processing across real-world teleoperation and synthetic datasets.
• Collaborate with a team building general-purpose Physical AI.

Skills

Python

Go

Large-scale data pipelines

Distributed systems

Tools

Spark

Kafka

Kubernetes

Terraform

Job description

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