Sr. SDE- ML Data Infrastructure, Frontier AI Robotics

About the role

Build and maintain scalable data infrastructure to support cutting-edge AI robotics research. Design dataset management systems including automated pipelines for data ingestion, processing, and curation. Develop visualization and inspection tools for dataset exploration and quality assessment. Research and implement state-of-the-art data filtering techniques including deduplication, quality scoring, and model-based filtering methods. Collaborate directly with science teams to support research projects through both infrastructure development and hands-on technical contribution to data preparation workflows.

About the team

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. We're leveraging 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.

Basic Qualifications

• 5+ years of non-internship professional software development experience
• 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
• Experience as a mentor, tech lead or leading an engineering team
• Strong software engineering background with full-stack development experience
• Deep understanding of machine learning fundamentals, particularly large-scale model training
• Expertise in distributed systems, cloud computing, and scalable data processing
• Experience with data pipeline design, ETL processes, and data management systems
• Proficiency in translating academic concepts into production systems

Preferred Qualifications

• 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations 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
• Background in research environments or supporting ML research workflows
• Experience with data visualization and annotation tooling
• Familiarity with modern data filtering and deduplication methodologies

Pay

The base pay for this position ranges from $151,300/year in our lowest geographic market up to $261,500/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience.