Staff Engineer, Robotics Data Platform

Amazon; Seattle (WA); On-site; USD 150,000 - 300,000; Full time

Job summary

Frontier AI & Robotics is building the future of intelligent robotics using frontier foundation models and end-to-end learned systems. We seek engineers to build scalable data infrastructure powering manipulation research and research workflows across a modern cloud-native stack.

You will collaborate with researchers and platform engineers to turn raw data into trainable episodes, maintaining end-to-end data pipelines, ingestion, and quality controls for scalable experimentation and deployment.

Qualifications

• 5+ years of non-internship software development experience.
• 5+ years owning the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience.
• Strong software engineering background with full-stack development experience.
• Expertise in distributed systems, cloud computing, and scalable data processing.
• Experience with data pipeline design, ETL processes, and data management systems.

Responsibilities

• Build and maintain the data infrastructure powering robotics manipulation research.
• Work with platform engineers to extend systems turning raw robot session data into curated, trainable episodes.
• Operate streaming ingestion, schema design, and data quality controls for researchers to use.

Skills

Full-stack

Distributed systems

Cloud computing

Data pipelines

ETL processes

Education

Bachelor's degree in Computer Science or equivalent

Tools

Kubernetes

TypeScript/React

Job description

Frontier AI & Robotics is building the future of intelligent robotics using frontier foundation models and end-to-end learned systems. We seek engineers to build scalable data infrastructure powering manipulation research and research workflows across a modern cloud-native stack.

You will collaborate with researchers and platform engineers to turn raw data into trainable episodes, maintaining end-to-end data pipelines, ingestion, and quality controls for scalable experimentation and deployment.