Member of Technical Staff - Infrastructure Engineer, Frontier AI & Robotics (FAR)

Job summary

Amazon’s Frontier AI & Robotics (FAR) team is seeking a Member of Technical Staff, Infrastructure to build and scale the foundational systems that power their robotics research and development platform. This role involves designing and operating distributed infrastructure to enable researchers and engineers to train foundation models, run large-scale experiments, and deploy intelligent robotic systems at Amazon scale. The position is deeply technical, focusing on performance, scalability, and reliability to support breakthrough research across FAR’s robotics ecosystem.

Qualifications

• 5+ years of distributed systems experience
• Bachelor's degree in Computer Science or a related field
• Proficiency in Python and at least one systems or backend programming language (e.g., Go, Java, C++)
• Experience with cloud infrastructure platforms (AWS, GCP, or Azure), including compute, storage, and networking services
• Experience building or maintaining data pipelines, ETL systems, or ML training/serving infrastructure
• Understanding of system reliability principles including monitoring, observability, fault tolerance, and on-call operational practices
• Experience supporting AI/ML research workflows, including building and optimizing training stack, experiment tracking, dataset management, or model deployment infrastructure
• Familiarity with robotics platforms, simulation environments, or real-time systems with strict latency requirements
• Experience with large-scale data processing frameworks (e.g., Apache Spark, Flink, or Ray) and query optimization for analytics workloads
• Demonstrated ability to lead large technical initiatives and influence architectural decisions across cross-functional teams
• Experience building developer tooling, internal platforms, or self-service infrastructure systems that improve research or engineering productivity

Responsibilities

• Design and build scalable compute and data infrastructure to support model training, inferencing, and evaluation for frontier AI/Robotics development
• Lead large technical initiatives and shape the architecture of FAR’s research platform infrastructure
• Develop tooling and frameworks that accelerate research workflows, including dataset management, visualization, and quality assessment systems
• Optimize query performance and data availability for experimentation and analytics workflows used by research teams
• Improve the performance, efficiency, and reliability of FAR’s core compute and storage infrastructure, ensuring systems remain fast and stable at scale
• Build highly scalable experimentation and analytics infrastructure to support model evaluation, A/B testing, and feature performance
• Collaborate directly with science and robotics teams to support research projects through infrastructure development and hands-on technical contribution

Skills

Degrees

Relocation