ML Engineer, Sequence Models & MLOps

Amazon; New York (NY); On-site; USD 140,000 - 210,000; Full time

Job summary

Amazon's Sequence Models team is building scalable ML infrastructure to accelerate research-to-production for sequence models across Amazon's products. You will design and implement systems that support data pipelines, training, and model serving at petabyte scale.

As a Machine Learning Engineer, you will partner with scientists to move experiments into production, optimize GPUs, reduce latency, and establish automated data quality checks, monitoring, and on-call processes for reliable ML

Responsibilities

• Build and scale ML infrastructure across data processing, distributed training, and model serving. Optimize GPU utilization, training throughput, serving latency, and Infra costs.
• Own the data pipelines that feed model training, including ingestion of structured and unstructured inputs, schema evolution, backfills, and data quality checks across upstream sources.
• 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.

Job description

Amazon's Sequence Models team is building scalable ML infrastructure to accelerate research-to-production for sequence models across Amazon's products. You will design and implement systems that support data pipelines, training, and model serving at petabyte scale.

As a Machine Learning Engineer, you will partner with scientists to move experiments into production, optimize GPUs, reduce latency, and establish automated data quality checks, monitoring, and on-call processes for reliable ML