4 jobs for "Staff ML Engineer - Ads ML Infrastructure"

Staff ML Engineer - Ads ML Infrastructure

At Apple - Cupertino

Posted on Oct 17

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Staff ML Engineer - Ads ML Infrastructure

At Apple - Cupertino

Posted on Oct 17

View job Apply on company site

Senior Staff Machine Learning Engineer, ML Platform

At Apple - Cupertino

Posted on Oct 19

View job Apply on company site

Senior Staff Machine Learning Engineer, ML Platform

At Apple - Cupertino

Posted on Oct 19

View job Apply on company site

Apple

Staff ML Engineer - Ads ML Infrastructure

Cupertino, CA$184,700 – $324,800Posted 21 days ago

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Why you should apply for a job to Apple:

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3.1/5 in supportive management
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65% would recommend this company to other women
66% say the CEO supports gender diversity

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At Apple, we work every day to create products that enrich people's lives. Our Ad Platforms group makes it possible for people around the world to easily access informative and imaginative content on their devices while helping publishers and developers promote and monetize their work. Today, our technology and services power advertising in Search Ads, App Store, and Apple News. Our platforms are highly-performant, deployed at scale, and setting new standards for enabling effective advertising while protecting user privacy.

The Machine Learning Platform team's mission is to empower Ad Platforms teams to build and scale the innovative ML systems that deliver highly optimized advertising content to consumers. Are you a results-oriented and versatile engineer who can excel in an Agile environment? You will work closely with engineers and data scientists to design, develop, and build world-class platform capabilities that will enable Ad Platforms teams to improve and scale our ML features, models, and applications.

Description

The ML Platform team is responsible for bringing numerous features to advertisers and consumers while simultaneously supporting scalable modeling and continuous experimentation by all Ad Platforms teams. As a key contributor to this team, you will design and develop secure and scalable back-end systems. You will enjoy building high-performing, elegant systems from the ground up, in close partnerships with various teams. You will also possess keen judgment in selecting technologies and building the right solution for the interesting challenges we get to tackle here. You will have the opportunity to define and refine architectures to meet the unique ad network challenges we must solve. You will play a meaningful role building machine learning products which deliver on Apple's privacy commitments and change the way advertising works with data.

Join us and contribute to a culture that emphasizes reliability, simplicity, and scalability. You will join a team of world-class machine learning engineers hungry to apply leading-edge technologies to deliver extraordinary experiences to our customers. We are one team, nurturing each other's growth and supporting each other in delivering for our customers!

Preferred Qualifications

PhD, MS, or BS in computer science or a related field, with 8+ years of experience in machine learning and strong software engineering skills.

Minimum Qualifications

Proven track record of designing and operating large-scale, low-latency ML Serving platform supporting real-time and batch inference.

Experience of model quantization, tensor parallelism, and inference optimizations (e.g ONNX Runtime, TensorRT, vLLM). Actively led evaluation and adoption of such technologies.

Experience working on distributed systems (e.g Ray, high-throughput RPC systems) to support scalable inference workloads and hybrid online/offline serving patterns.

Hands-on experience designing and optimizing low-level GPU kernels to maximize hardware utilization, bypass memory bandwidth bottlenecks, and accelerate deep learning primitives.

Prior experience in advertising industry, federated learning and privacy-preserving ML techniques.

Recognized as a technical leader and mentor, supports the growth of engineers through code/design reviews, working groups, and internal knowledge sharing.

Led development of foundational AI/ML platforms and tooling including Feature Stores, Vector DB to accelerate team productivity and model lifecycle management.

Experience performance tuning & trouble-shooting.

Passionate about developer experience builds abstractions, automation tools, and reusable components to streamline ML workflows and reduce operational burden.

Ability to communicate effectively, both written and verbal, with technical and non-technical multi-functional teams.

Results oriented with a desire to work in a fast-paced and collaborative work environment.

Pay & Benefits

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 $184,700 and $324,800, 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.

About Apple

Working at Apple means doing more than you ever thought possible and having more impact than you ever imagined.

Size: 10,000+ employees
Industry: Technology: Manufacturing

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