ML Engineer, Ads Performance Intelligence & GenAI

Amazon; Seattle, Northern (WA, KY); Hybrid; USD 144,000 - 194,000; Full time

Benefits offered by this job

Health insurance

RSUs

401(k) matching

Parental leave

Job summary

Amazon is seeking a Machine Learning Engineer to develop, deploy, and scale robust ML and GenAI solutions in production. You will own building ML infra for production models, partnering with scientists, engineers, and product teams to deliver automated decisioning.

You will work across data, ML, and engineering disciplines, shaping training workflows, monitoring, and optimization while leveraging tools like AWS Bedrock, SageMaker, and LangChain to drive innovation at scale.

Qualifications

• 3+ years of non-internship professional software development experience.
• 2+ years of non-internship design or architecture of scalable systems.
• Experience in machine learning, data mining, information retrieval, statistics or NLP.
• Experience in at least one programming language.

Responsibilities

• Collaborate with Data and Applied Scientists to process data and scale ML/LLM infra while optimizing Infra costs.
• Create reusable technical assets to accelerate ML, Optimization and GenAI adoption across initiatives.
• Design and maintain production grade large-scale distributed training systems for ML/GenAI models.
• Optimize AWS infra costs, GPU utilization, latency and fine-tuning on large datasets.
• Develop robust monitoring and debugging tools for training workflows.
• Collaborate to prototype GenAI/ML models and evaluate technical feasibility.

Skills

Software development

System design

ML/AI

Programming languages

Education

Bachelor's degree in CS or equivalent

Tools

AWS Bedrock

SageMaker

LangChain

Containerization

Job description

Amazon is seeking a Machine Learning Engineer to develop, deploy, and scale robust ML and GenAI solutions in production. You will own building ML infra for production models, partnering with scientists, engineers, and product teams to deliver automated decisioning.

You will work across data, ML, and engineering disciplines, shaping training workflows, monitoring, and optimization while leveraging tools like AWS Bedrock, SageMaker, and LangChain to drive innovation at scale.