ML Platform SRE — Scale Apple Ads Infra

Apple Inc.; New York, Northern (NY, KY); Hybrid; USD 150,000 - 225,000; Full time

Benefits offered by this job

Relocation assistance

Job summary

Apple Inc. in New York City is seeking a Site Reliability Engineer focused on machine learning to scale and maintain the ML platform powering Apple Ads. You will own health, performance, and reliability of large-scale infrastructure, building automation to reduce toil and accelerate product delivery.

The role requires deep knowledge of distributed systems, AWS services, and IaC, with collaboration across ML, data science, and Ads engineering teams to drive production excellence.

Qualifications

• 3+ years in internet-facing backend production systems, SRE or ML Ops on large-scale distributed cloud infra.
• Proven expertise with AWS-managed infrastructure.
• Experience with ML lifecycle tools (NVIDIA Triton, Ray, Apache Airflow, etc.).
• Strong programming in Python, Java, Rust, Go or similar.
• Hands-on experience with Linux systems and deep knowledge of its internals.
• Terraform and Infrastructure as Code experience.
• Strong SRE fundamentals: monitoring, incident response, SLOs, and reliability.

Responsibilities

• Build and operate distributed systems on AWS (EKS, ElasticCache, ML tools).
• Develop tooling to improve reliability, cost-efficiency, and operational visibility.
• Collaborate with engineering teams to define infra architecture and troubleshoot issues.
• Design and manage Infrastructure as Code with Terraform, ensuring repeatable deployments.
• Lead or participate in incident response, postmortems, and continuous improvement.

Skills

AWS

Python

Go

Linux

Terraform

Monitoring & SLOs

Distributed systems

Tools

Kubernetes

Ray

NVIDIA Triton

Apache Airflow

Job description

Apple Inc. in New York City is seeking a Site Reliability Engineer focused on machine learning to scale and maintain the ML platform powering Apple Ads. You will own health, performance, and reliability of large-scale infrastructure, building automation to reduce toil and accelerate product delivery.

The role requires deep knowledge of distributed systems, AWS services, and IaC, with collaboration across ML, data science, and Ads engineering teams to drive production excellence.