Senior AI Data-Preparation Platform Engineer

Amazon Inc.; Seattle (WA); Vor Ort; USD 168.000 - 227.000; Vollzeit

Zusammenfassung

Amazon's SageMaker team in Seattle is seeking a Sr. SDE to build AI-powered data preparation systems that scale labeling, verification, and LLM-driven evaluation for ML datasets.

You will architect components for auto-labeling, human-in-the-loop workflows, and model quality, partnering with ML science teams to push the boundaries of data quality at scale. This role offers high visibility and impactful work across AWS.

Qualifikationen

• 5+ years of non-internship professional software development experience.
• 5+ years of programming with at least one software programming language.
• 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
• 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 building ML pipelines, data processing systems, or evaluation infrastructure at scale
• Hands-on experience with LLMs (prompting, fine-tuning, structured output, confidence calibration)

Aufgaben

• Data Preparation Platform: Design and deliver core components of data preparation journey to customize and fine-tune LLMs in SageMaker, designing systems that provide customers with high-quality, reliable data for their ML workflows.
• Drive Innovation in Data Preparation: Build and scale systems leveraging auto-labeling and LLM-as-Judge techniques to automatically detect, diagnose, and remediate data quality issues.
• Agent & Model Quality: Establish quality standards and evaluation frameworks for AI agents and models, implementing continuous improvement processes.
• Human-in-the-Loop Services: Lead the evolution of our HITL suite, enabling seamless human feedback loops for data labeling, annotation quality assurance, and ground truth generation.
• Technical Leadership: Mentor engineers, drive design reviews, and raise the engineering quality bar across the team. Influence technical direction without formal authority.
• Architecture & Strategy: Make high-judgment architectural decisions across distributed systems, data processing, and ML infrastructure. Own the technical roadmap for your area.

Kenntnisse

Non-internship software development

Mentor / tech lead

ML pipelines

Ausbildung

Bachelor's degree in computer science or equivalent

Tools

LLMs (prompting, fine-tuning)

Jobbeschreibung

Amazon's SageMaker team in Seattle is seeking a Sr. SDE to build AI-powered data preparation systems that scale labeling, verification, and LLM-driven evaluation for ML datasets.

You will architect components for auto-labeling, human-in-the-loop workflows, and model quality, partnering with ML science teams to push the boundaries of data quality at scale. This role offers high visibility and impactful work across AWS.