AI Training Data & Platform Engineer

Amazon; Seattle (WA); On-site; USD 144,000 - 194,000; Full time

Benefits offered by this job

Health insurance

RSUs (restricted stock units)

401(k) matching

Paid time off

Parental leave

Job summary

Amazon is seeking a Software Development Engineer to design, build, and operate scalable systems that transform real customer interactions into high-quality datasets, signals, and insights for model training, post-training, and evaluation.

You will partner with applied scientists to refine metrics, analyze experiments, and translate findings into robust data recipes and learning signals, while building automated workflows for continuous model improvement with strong emphasis on privacy and

Qualifications

• 3+ years of non-internship professional software development experience.
• Experience with large-scale data platforms or analytics.
• Experience defining metrics and data quality monitoring.
• Knowledge of ML workflows, training data preparation, evaluation, and model behavior analysis.

Responsibilities

• Design, build, and operate scalable systems transforming real customer interactions into datasets, signals, and insights for model training and evaluation.
• Develop data intelligence capabilities to analyze customer behavior and improve ML models.
• Build pipelines and tools for data ingestion, filtering, sampling, and dataset generation; ensure quality and validation.
• Partner with applied scientists to define metrics, analyze experiments, and translate findings into data recipes and learning signals.
• Develop automated workflows for data curation, anomaly detection, experimentation, evaluation, and continual model improvement with privacy and security in mind.

Skills

Software development

Distributed systems

Machine learning basics

LLM fundamentals

Programming languages

Education

Master's degree in engineering/CS/ ML or equivalent

GSEC (GIAC Security Essentials)

Tools

Spark

Flink

SQL

Job description

Amazon is seeking a Software Development Engineer to design, build, and operate scalable systems that transform real customer interactions into high-quality datasets, signals, and insights for model training, post-training, and evaluation.

You will partner with applied scientists to refine metrics, analyze experiments, and translate findings into robust data recipes and learning signals, while building automated workflows for continuous model improvement with strong emphasis on privacy and