ML Platform SRE: Scale-Ready Infra for Ads

Socket.dev; New York (NY); On-site; USD 140,000 - 210,000; Full time

Job summary

Apple Ads seeks a ML Platform Infrastructure Engineer to scale ML training, inference, and serving workloads. You’ll own health, performance, and automation of large-scale AWS-based infrastructure powering Apple Ads applications, building platform solutions rather than just pipelines.

Ideal candidates have 3+ years in SRE/ML Ops, strong coding in Python/Java/Rust/Go, and IaC with Terraform, plus expertise in Linux and observability concepts.

Qualifications

• 3+ years in internet-facing backend production systems, SRE or ML Operations on large-scale cloud infra.
• Experience with AWS-managed infrastructure and scalable services.
• Familiarity with ML lifecycle tools such as NVIDIA Triton, AnyScale Ray, Apache Airflow.
• Strong programming skills in Python, Java, Rust or Go.
• Hands-on Linux and deep knowledge of its internals.
• IaC experience, especially Terraform.
• Solid grounding in SRE: monitoring, alerting, observability, incident response, error budgets, SLAs/SLOs.

Responsibilities

• Own health, performance, and scalability of ML training, inference, serving workloads and platform tooling.
• Build automation to reduce toil, improve resilience, and speed up delivery.
• Develop platform solutions beyond basic CI/CD pipelines.
• Collaborate across engineering, infrastructure, and data science teams.

Skills

AWS

ML Ops

Python

Java

Rust

Go

Terraform

Linux

Monitoring

Incident response

Tools

NVIDIA Triton

Apache Airflow

AnyScale Ray

Kubernetes

Job description

Apple Ads seeks a ML Platform Infrastructure Engineer to scale ML training, inference, and serving workloads. You’ll own health, performance, and automation of large-scale AWS-based infrastructure powering Apple Ads applications, building platform solutions rather than just pipelines.

Ideal candidates have 3+ years in SRE/ML Ops, strong coding in Python/Java/Rust/Go, and IaC with Terraform, plus expertise in Linux and observability concepts.