Senior ML Architect: Large-Scale AI Systems Lead

Amazon.com Services LLC; Bellevue (WA); On-site; USD 350,000 - 650,000; Full time

Benefits offered by this job

Sign-on payments

Restricted stock units (RSUs)

Health insurance (medical, dental, and

401(k) matching

Paid time off

Parental leave

EAP

Job summary

Amazon.com Services LLC seeks a Senior ML technical leader to shape architecture and strategy for large-scale AI services, including generative AI and LLMs. You will design complex ML systems, build reusable platforms, and drive production-grade ML serving with reliability and low latency.

You will mentor L4/L5 ML engineers, influence cross-team architecture decisions, and push best practices across the org while championing responsible AI and cost optimization.

Qualifications

• 5+ years of professional software development and architecture experience.
• Experience leading design or architecture of large, scalable systems.
• Mentor or tech-lead experience within engineering teams.
• Experience building ML/AI systems and deployment for production.

Responsibilities

• Define ML technical strategy and architecture for multiple teams.
• Design and lead multi-model ML systems at scale.
• Architect ML platforms enabling rapid experimentation and deployment.
• Lead real-time and batch ML serving infra with high availability and low latency.
• Promote MLOps, governance, responsible AI, and cost optimization.

Skills

ML architecture

Technical leadership

Distributed systems

MLOps

RLHF

Foundation models

RAG

Deployment

Cost optimization

Mentoring

Cloud scale

Education

Bachelor’s degree in computer science or related field

Job description

Amazon.com Services LLC seeks a Senior ML technical leader to shape architecture and strategy for large-scale AI services, including generative AI and LLMs. You will design complex ML systems, build reusable platforms, and drive production-grade ML serving with reliability and low latency.

You will mentor L4/L5 ML engineers, influence cross-team architecture decisions, and push best practices across the org while championing responsible AI and cost optimization.