Site Reliability Engineer, ML

Apple Inc

Confirmed live 2 days ago High trust

Quick summary

Work type: On-site
Location: New York, NY
Salary: $150,400–$225,300 / yr
Posted: 52 days ago
Freshness: Confirmed live 2 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $210k

This role $188k

$136k $284k

below market most similar roles pay here above market

This role pays less than 69% of similar roles. Most pay $171,575–$248,487 — the blue band above. At the midpoint, this role pays about $188k versus about $210k for comparable roles.

Based on 240 similar postings.

Employer

About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 3535 open roles on FindRole.

Listed pay typically runs $166,600–$277,600 across 2738 roles with salary data.

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At a glance

TL;DR · Site Reliability Engineer, ML

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The Site Reliability Engineer - ML, Apple Ads joins the Site Reliability Engineering team to ensure the reliability, performance, and availability of the ML Platform and Services. This role involves building and evolving the next generation of machine learning platform infrastructure to support transactional and analytical workloads. You will own the health of large-scale infrastructure for ML training, inference, and serving workloads by building automation to eliminate manual processes. Key responsibilities include building distributed systems using AWS managed services like EKS, ElasticCache, and ML technologies including Ray over Kubernetes and NVIDIA Triton Inference Server. You will use Terraform for Infrastructure as Code and develop internal tooling. Required skills include Python, Java, Rust, or Go, Linux internals, and experience with Apache Airflow and GPU hardware architectures.

What does a Site Reliability Engineer earn?

Median $187850 from 115 postings across 33 companies.

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Skills

AWS Kubernetes Terraform Python Java Rust Go EKS Ray NVIDIA Triton Inference Server Apache Airflow Linux ElasticCache Infrastructure as Code Distributed Systems Monitoring Observability SRE

What you'll do

Build and operate distributed systems using AWS managed services like EKS and ElasticCache.
Deploy and manage ML technologies including Ray over Kubernetes and NVIDIA Triton Inference Server.
Develop internal tooling and automation frameworks to improve infrastructure reliability and cost-efficiency.
Design and manage Infrastructure as Code using Terraform for repeatable and secure deployments.
Lead incident response efforts and conduct postmortems to drive continuous system improvements.
Troubleshoot complex issues in large-scale distributed systems supporting ML training and inference workloads.
Monitor and maintain the health, performance, and scalability of ML platform infrastructure.

What we're looking for

3+ years of experience in internet-facing backend production systems, SRE, or ML Operations roles on large scale distributed cloud infrastructure.
Proven expertise with AWS-managed infrastructure.
Familiarity with ML lifecycle and technologies such as NVIDIA Triton, AnyScale Ray, and Apache Airflow.
Strong programming skills in at least one of Python, Java, Rust, Go, or similar languages.
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, and SLAs/SLOs.
Experience managing Kubernetes clusters at scale, troubleshooting distributed systems, or understanding GPU hardware and high-performance fabrics (preferred).

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