Member of Technical Staff - Data Platform Engineer, Frontier AI Robotics

Description
At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up. Our team is building the future of intelligent robotics through frontier foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios.

Description
At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up. Our team is building the future of intelligent robotics through frontier foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios.

What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's massive computational infrastructure and rich real-world datasets to train and deploy state‑of‑the‑art foundation models. Our work spans the full spectrum of robotics intelligence – from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real‑world scenarios.

We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations.

Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world‑class researchers, and seeing your innovations deployed at unprecedented scale.

In this role you will build and maintain the data infrastructure that powers our robotics manipulation research. You'll work alongside our existing team of platform engineers to extend the systems that turn raw robot session data into curated, trainable episodes. This team owns streaming ingestion pipelines, platform and schema design, heterogeneous data sources, data curation and quality controls, full‑stack inspection and dataset‑builders that researchers and human annotators actually use, and tools to let scientists go from dataset to training job without leaving the platform.

We run on a modern cloud‑native stack — distributed compute on Kubernetes, streaming data infrastructure, columnar lakehouse storage, and a Type Script/React frontend. We’re looking for engineers willing and eager to work on the full stack in a fast iteration cycle while working with researchers as close customers.

What matters is that you can ship full‑stack data infrastructure real users depend on, treat researchers as collaborators rather than customers, and have a strong bias toward iteration in a flat org where engineers pick up science‑driven work directly instead of waiting for approval layers.

• 5+ years of non‑internship professional software development experience
• 5+ years of 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

• Experience as a mentor, tech lead or leading an engineering team
• 5+ years of programming with at least one software programming language experience
• 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
• Bachelor's degree in computer science or equivalent
• Experience with dataset curation and quality assessment techniques Knowledge of computer vision and multimodal data processing
• Deep understanding of machine learning fundamentals, particularly large‑scale model training
• Background in research environments or supporting ML research workflows
• Experience with data visualization and annotation tooling
  
  Familiarity with modern data filtering and deduplication methodologies
• Proficiency in translating academic…