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

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

Job :  |  Services LLC

At Frontier AI & Robotics, we are reimagining robotics from the ground up. Our team builds the future of intelligent robotics through frontier foundation models and end‑to‑end learned systems, tackling complex perception and manipulation challenges in real‑world scenarios. We leverage Amazon’s massive computational infrastructure and rich real‑world datasets to train and deploy state‑of‑the‑art foundation models that scale across Amazon’s global operations.

In this role, you will build and maintain the data infrastructure that powers our robotics manipulation research. You will work with a platform engineering team to extend pipelines that convert raw robot session data into curated, trainable episodes. The team owns streaming ingestion pipelines, platform and schema design, heterogeneous data sources, data curation and quality controls, full‑stack inspection, dataset builders used by researchers and annotators, and tools that enable scientists to go from dataset to training job without leaving the platform.

You will work on a modern cloud‑native stack featuring Kubernetes, streaming data infrastructure, a columnar lakehouse storage, and a Type Script/React frontend. You should be able to ship full‑stack data infrastructure that real users depend on, collaborate closely with researchers, and iterate rapidly in a flat organization.

• 5+ years of professional software development experience (non‑internship)
• 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 in leading an engineering team
• 5+ years of programming with at least one software programming language
• 5+ years of leading design or architecture of new and existing systems, including design patterns, reliability, and scaling
• 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 concepts into production systems

The base pay for this position ranges from $150,000/year in our lowest geographic market up to $300,000/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. In addition to base salary, equity, sign‑on payments, and other forms of compensation may be provided as part of the total compensation package, as well as medical, financial, and other benefits.

For more details, visit the Amazon employee benefits page.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Pursuant to the Los Angeles County Fair Chance Ordinance and the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records.

Los Angeles County applicants:
Job duties for this position include working safely and cooperatively with other employees, supervisors, and staff; adhering to standards of excellence; communicating effectively; and following all federal, state, and local laws and company policies. Criminal history may be considered in relation to some material job duties, including adherence to company policies, exercise of sound judgment, effective stress management, and safeguarding the company’s reputation.