Amazon Jobs
Sr. SDE- ML Data Infrastructure, Frontier AI Robotics
Amazon Jobs, San Francisco, California, United States, 94199
Overview
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. 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. Responsibilities
Design, build, and maintain scalable data infrastructure to support AI robotics research. Create dataset management systems with automated data ingestion, processing, and curation pipelines. Develop visualization and inspection tools for dataset exploration and quality assessment. Research and implement data filtering techniques, including deduplication, quality scoring, and model-based filtering methods. Collaborate with science teams to support research projects through infrastructure development and hands-on data preparation workflows. Qualifications
5+ years of non-internship professional software development experience. 5+ years of programming experience in at least one software language. 5+ years of experience in design or architecture of new and existing systems with emphasis on reliability and scaling. 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. Full software development life cycle experience, including coding standards, code reviews, source control, build processes, testing, and operations. 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. Amazon is an equal opportunity employer and does not discriminate on the basis of protected status. Pursuant to local fair chance ordinances, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please note that accommodations are available.
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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. 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. Responsibilities
Design, build, and maintain scalable data infrastructure to support AI robotics research. Create dataset management systems with automated data ingestion, processing, and curation pipelines. Develop visualization and inspection tools for dataset exploration and quality assessment. Research and implement data filtering techniques, including deduplication, quality scoring, and model-based filtering methods. Collaborate with science teams to support research projects through infrastructure development and hands-on data preparation workflows. Qualifications
5+ years of non-internship professional software development experience. 5+ years of programming experience in at least one software language. 5+ years of experience in design or architecture of new and existing systems with emphasis on reliability and scaling. 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. Full software development life cycle experience, including coding standards, code reviews, source control, build processes, testing, and operations. 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. Amazon is an equal opportunity employer and does not discriminate on the basis of protected status. Pursuant to local fair chance ordinances, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please note that accommodations are available.
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