Machine Learning Engineer, Sequence Models (project Sequoia)

Sourced from emploive.com

Amazon's Sequence Models team builds centralized sequence models that understand customer journeys across all Amazon products (Stores, Prime Video, Audible, Music, Twitch) to unlock insights that optimize the customer experience, including ad serving. As a Machine Learning Engineer, you will streamline the model development lifecycle from research to production by building ML infrastructure and establishing MLOps practices. You will solve complex challenges at petabyte scale and enable rapid experimentation and deployment of ML models.

• Build and scale ML infrastructure across data processing, distributed training, and model serving
• Optimize GPU utilization, training throughput, serving latency, and infrastructure costs
• Own data pipelines feeding model training, including ingestion of structured and unstructured inputs, schema evolution, backfills, and data quality checks
• Partner with Applied Scientists to shorten the time from experiment to production
• Evolve model serving and feature delivery to support continuous experimentation
• Establish automated, repeatable processes for large-scale data analysis, model training, validation, and deployment
• Own operational excellence for high-volume, low-latency production systems, including monitoring, alarming, troubleshooting, and on-call