Site Reliability Engineer - ML, Apple Ads

Apple, Inc.; New York (NY); On-site; USD 150,000 - 225,000; Full time

Benefits offered by this job

Medical and dental coverage

Employee stock programs

Relocation assistance

Tuition reimbursement

Discretionary bonuses

Job summary

Apple Inc. in New York City is seeking a Site Reliability Engineer focused on ML to own the health, performance, and scalability of large-scale ML infrastructure powering Apple Ads. You will build automation to reduce manual toil and boost platform resilience.

The role involves partnering with Ads, data science, and ML platform teams, deploying via Terraform, and operating across AWS environments. A strong ML lifecycle background is essential.

Qualifications

• 3+ years 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 associated technologies such as NVIDIA Triton, AnyScale Ray, Apache Airflow etc.
• Strong programming skills in 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: Monitoring, alerting, observability, Incident response and root cause analysis, Error budgets, SLAs/SLOs, and system reliability

Responsibilities

• Build and operate distributed systems using AWS managed services such as EKS, ElasticCache and ML technologies like Ray over Kubernetes and NVIDIA Triton Inference Server.
• Develop internal tooling and automation frameworks to improve infrastructure reliability, cost-efficiency, and operational visibility.
• Collaborate with engineering teams to define infrastructure architecture, troubleshoot complex issues, and drive production excellence.
• Design and manage Infrastructure as Code with Terraform, ensuring repeatable, secure, and scalable deployments.
• Lead or participate in incident response, postmortems, and continuous improvement cycles to reduce future risk.

Skills

AWS

Kubernetes

Terraform

Python

Java

Go

Linux

Ray

NVIDIA Triton

Apache Airflow

Monitoring/Observability

SRE fundamentals

Tools

Terraform

Ray

NVIDIA Triton

Apache Airflow

EKS

Job description

Site Reliability Engineer - ML, Apple Ads

New York City, New York, United States Software and Services

At Apple, we focus deeply on our customers’ experience. Apple Ads brings this same approach to advertising, helping people find exactly what they’re looking for and helping advertisers grow their businesses.Our technology powers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS Season Pass. Everything we do is designed for trust, connection, and impact: We respect user privacy, integrate advertising thoughtfully into the experience, and deliver value for advertisers of all sizes—from small app developers to big, global brands. Because when advertising is done right, it benefits everyone.

The Site Reliability Engineering team within Apple Ads ensures the reliability, performance, and availability of ML Platform and Services at scale. The team partners closely with Ads engineering, data science and ML platform teams to enable product delivery through design, configuration, and automation of machine learning infrastructure powering Apple Ads applications.

We are looking for a ML Platform Infrastructure Engineer to help build and evolve the next generation of Apple Ads machine learning platform — enabling fast, reliable, and scalable operations across AWS-based environments supporting transactional and analytical workloads.

Description

As a site reliability engineer in Apple Ads focused on machine learning, you will own the health, performance, and scalability of large scale infrastructure powering ML training, inference, serving workloads and associated platform tooling. Your focus will be on building automation that eliminates manual processes, improves platform resilience, and enables teams to move faster with confidence.This is not a DevOps-only or CI/CD-focused role. We are looking for engineers who build platform solutions, not just configure pipelines.

Responsibilities

• Build and operate distributed systems using AWS managed services such as EKS, ElasticCache and ML technologies like Ray over Kubernetes and NVIDIA Triton Inference Server.


• Develop internal tooling and automation frameworks to improve infrastructure reliability, cost-efficiency, and operational visibility.


• Collaborate with engineering teams to define infrastructure architecture, troubleshoot complex issues, and drive production excellence.


• Design and manage Infrastructure as Code with Terraform, ensuring repeatable, secure, and scalable deployments.


• Lead or participate in incident response, postmortems, and continuous improvement cycles to reduce future risk.

Minimum Qualifications

• 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 associated technologies such as NVIDIA Triton, AnyScale Ray, Apache Airflow etc.


• 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: Monitoring, alerting, observability, Incident response and root cause analysis, Error budgets, SLAs/SLOs, and system reliability

Preferred Qualifications

• Built 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 is a plus.


• Understanding of modern GPU hardware architectures (such as NVIDIA H100, B200, or GB200, AWS Inferentia ), associated drivers


• Understanding of high-performance fabrics and network architecture, power, and thermal limits

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $150,400 and $225,300, and your base pay will depend on your skills, qualifications, experience, and location.

• Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan.


• You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition.


• Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.
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