SDE II: ML Infra – Capacity, Scheduling & Fleet Orchestration

Amazon Web Services (AWS); Seattle (WA); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Sign-on payments

Restricted stock units (RSUs)

Health insurance

Medical insurance

Dental insurance

Vision insurance

Prescription insurance

Basic Life & AD&D insurance

Supplemental life plans

EAP

Mental Health Support

Medical Advice Line

Flexible Spending Accounts

Adoption and Surrogacy Reimbursement

401(k) matching

Paid time off

Parental leave

Job summary

Amazon Web Services (AWS) seeks a lead engineer to design and implement an ML infrastructure platform focusing on capacity management, workload scheduling, and fleet orchestration. You will collaborate with ML scientists and hardware teams to ensure seamless accelerator access and high utilization.

Qualifications include 3+ years of software development and 2+ years of system design, with proficiency in Go, Java, or Python and Kubernetes or container ecosystems highly preferred.

Qualifications

• Requires 3+ years of professional software development and 2+ years of system design experience.
• Proficiency in Go, Java, or Python and experience with Kubernetes or container ecosystems is highly preferred.

Responsibilities

• Lead the design and implementation of an ML infrastructure platform focused on capacity management, workload scheduling and fleet orchestration.
• Collaborate with ML scientists and hardware teams to ensure seamless accelerator access and high utilization.
• Drive performance profiling and optimization across the platform to improve resource efficiency.

Skills

Machine Learning Infra

Capacity Management

Workload Scheduling

Fleet Orchestration

Profiling & Optimization

Resource Management

Code Generation

Kubernetes

Docker

Go

Java

Python

CI/CD

System Architecture

Tools

Kubernetes

Docker

Job description

Amazon Web Services (AWS) seeks a lead engineer to design and implement an ML infrastructure platform focusing on capacity management, workload scheduling, and fleet orchestration. You will collaborate with ML scientists and hardware teams to ensure seamless accelerator access and high utilization.

Qualifications include 3+ years of software development and 2+ years of system design, with proficiency in Go, Java, or Python and Kubernetes or container ecosystems highly preferred.