Site Reliability Engineer - ML, Apple Ads at Apple

Department: Software and Services

Compensation · Listed in posting

$150,400 – $225,300

Location: New York, New York
Level: mid
Posted: Sep 9, 2026

Description

Apple Ads is hiring an ML Platform Infrastructure Engineer to build and operate reliable, scalable machine learning infrastructure on AWS. The role focuses on distributed systems, ML training and inference workloads, automation, infrastructure as code, observability, incident response, and platform resilience. It requires at least three years of experience in large-scale distributed cloud infrastructure, AWS expertise, programming ability, Linux knowledge, and Terraform experience.

Required Skills

AWS infrastructure
EKS
Ray
NVIDIA Triton
Terraform
Python
Linux
Kubernetes

Additional Information

Required Previous Experiences: 3+ years of experience in internet-facing backend production systems, SRE or ML Operations focused roles on large-scale distributed cloud infrastructure
Proven expertise with AWS-managed infrastructure
Familiarity with ML lifecycle and technologies including NVIDIA Triton, AnyScale Ray, and Apache Airflow
Strong programming skills in Python, Java, Rust, Go, or a similar language
Hands-on experience with Linux systems and deep knowledge of its internals
Demonstrated experience with Infrastructure as Code, especially Terraform
Strong foundation in SRE concepts including monitoring, alerting, observability, incident response, root cause analysis, error budgets, SLAs/SLOs, and system reliability
Preferred Qualifications: Experience building tools or services that automate platform operations, reduce toil, or improve cost efficiency
Experience managing Kubernetes clusters at scale in production environments
Hands-on experience troubleshooting distributed systems under real-world load
Clear communication skills and comfort collaborating across engineering, infrastructure, and product teams
AWS certifications or broad experience across multiple AWS services
Understanding of modern GPU hardware architectures and associated drivers
Understanding of high-performance fabrics, network architecture, power, and thermal limits

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