Sr Machine Learning Engineer - ML Platform

Apple Inc.; New York (NY); On-site; USD 185,000 - 278,000; Full time

Benefits offered by this job

Stock programs

Relocation assistance

Education reimbursement

Employee stock purchase plan

Job summary

Apple Inc. in New York City seeks a world-class ML Platform Engineer to design and build scalable back-end systems for Ads ML features.

You will work with ML engineers to deploy models, optimize pipelines, and ensure privacy-preserving, high-performance AI for advertising at scale.

Qualifications

• Experience writing mission-critical code for production ML systems.
• Experience building ML infrastructure, frameworks or services used by multiple teams.
• Experience building SDKs, API, and automation UIs for developers.
• Proven experience building automation and CI/CD pipelines.
• Passion for improving the developer experience for AI/ML practitioners.
• Solid understanding of the ML lifecycle: training, evaluation, deployment and serving/inferencing.
• Understanding of model evaluation, train-serve skew and data drift.
• Hands-on with PyTorch or TensorFlow in real deployments.
• Experience applying ML at scale in advertising or related domains.
• Strong problem solving, debugging and performance tuning skills.
• Clear, effective written and verbal communication across teams.
• Product-minded with ownership of projects.

Responsibilities

• Design and develop secure, scalable back-end ML platform capabilities.
• Collaborate with ML engineers and scientists to deliver ML features end-to-end.

Skills

Mission-critical code

ML infrastructure

SDKs & APIs

CI/CD automation

Developer experience

ML lifecycle

Model evaluation & data drift

PyTorch/TensorFlow

ML at scale in advertising

Diagnostics & performance tuning

Communication & collaboration

ownership & results orientation

Education

PhD in Computer Science or related field with 3+ years of engineering experience and 5+ years of machine learning experience

MS in Computer Science or related field with 6+ years of engineering experience and 5+ years of ML experience

BS in Computer Science or related field with 7+ years of engineering experience and 5+ years of ML experience

Tools

PyTorch

TensorFlow

Job description

New York City, New York, United States Machine Learning and AI

At Apple, we work every day to create products that enrich people's lives. Our Apple Ads 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 the App Store, Apple Maps, and Apple News. Our platforms are highly-performant, deployed at scale, and setting new standards for enabling effective advertising while protecting user privacy.The Apple Ads Machine Learning Platform team's mission is to empower Ads 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 a fast-paced environment? You will work closely with ML engineers and scientists to design, develop, and build world-class platform capabilities that will enable Ads 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 Ads 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 solutions for the unique ad network challenges we face. 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!

Minimum Qualifications

• Experience writing mission-critical code for production machine learning systems
• Experience building ML infrastructure, frameworks or services used by multiple teams
• Experience building SDKs, API, and automation UIs used by development teams
• Proven experience building automation and CI/CD
• Passionate about improving the developer experience for AI/ML practitioners
• Solid understanding of the ML lifecycle: training, evaluation, deployment and serving/inferencing, with working experience building and deploying models
• Solid understanding of model evaluation, train-serve skew and data drift
• Working knowledge of deep learning architectures and training frameworks such as PyTorch or TensorFlow
• Prior experience applying ML at scale in advertising, recommender systems, information retrieval or related domains
• Strong problem solving, debugging and performance tuning skills
• Results oriented, with the ability to communicate effectively, both written and verbal, with technical and non-technical multi-functional teams
• Product-minded with a proven ability to seek projects with a sense of ownership

Preferred Qualifications

• Experience in advertising industry
• Experience with distributed training and/or optimizing large-scale models for low-latency serving
• Experience building infrastructure for diverse sets of model development use cases including LLMs, multimodal models, classical ML, and reinforcement learning.
• Experience building and/or operationalizing foundation models
• Experience with agentic AI
• Prior experience in privacy-preserving ML
• Education & Experience
• PhD in Computer Science or related field with 3+ years of engineering experience and 5+ years of machine learning experience; or MS in Computer Science or related field with 6+ years of engineering experience and 5+ years of machine learning experience; or BS in Computer Science or related field with 7+ years of engineering experience and 5+ years of machine learning experience

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 $277,600, 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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