Data Infrastructure

Genesis AI; United States; On-site; USD 140,000 - 210,000; Full time

Job summary

Genesis AI is seeking a senior data engineer to design, build, and maintain large-scale data pipelines for robotics foundation model training and evaluation.

You will own core data infrastructure, including data models, storage, ingestion, and orchestration, while standardizing processing across teleoperation and synthetic datasets. You’ll collaborate with a driven team to advance general-purpose Physical AI.

Qualifications

• 8+ years experience designing, building, and maintaining large-scale data pipelines.
• Deep understanding of distributed systems (e.g., Spark, Kafka).
• Experience with data storage technologies (data lakes, warehouses, object stores like S3).
• Experience running production-grade infrastructure (Kubernetes, Terraform).

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 to build general-purpose Physical AI.

Skills

Python/Go

Distributed systems

Data pipelines

Data storage

Tools

Kubernetes

Terraform

Spark

Kafka

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