Sr Machine Learning Engineer - ML Platform

Apple’s Ads Machine Learning Platform team is building secure, scalable platform capabilities that help power machine learning across advertising. In this role, you will collaborate with ML engineers and scientists to improve and scale ML features, models, and applications, while advancing Apple’s privacy commitments.

This position is based in New York, NY (onsite) and is designed for experienced engineers who enjoy building production systems and strengthening the developer experience for AI and ML practitioners.

What you’ll do

• Design and develop secure, scalable back-end systems for ML platform capabilities.
• Build high-performing systems with clean design, created from the ground up.
• Partner with ML engineers and scientists to design, develop, and deliver platform capabilities that help Ads teams improve and scale ML features, models, and applications.
• Contribute to ML product development that supports Apple’s privacy commitments and influences how advertising works with data.

Key requirements

• Production ML experience: experience writing mission-critical code for production machine learning systems.
• ML infrastructure background: experience building ML infrastructure, frameworks, or services used by multiple teams.
• Developer-facing tooling: experience building SDKs, APIs, and automation UIs used by development teams.
• Automation and CI/CD: proven experience building automation and CI/CD pipelines.
• Developer experience focus: passion for improving developer experience for AI/ML practitioners.
• ML lifecycle knowledge: solid understanding of training, evaluation, deployment, and serving/inference, with experience building and deploying models.
• Evaluation and reliability: solid understanding of model evaluation, train-serve skew, and data drift.
• Deep learning and frameworks: working knowledge of deep learning architectures and training frameworks such as PyTorch or TensorFlow.
• Applied ML at scale: prior experience applying ML at scale in advertising, recommender systems, information retrieval, or related domains.
• Execution strength: strong problem solving, debugging, and performance tuning skills.
• Communication and ownership: results oriented, able to communicate effectively with technical and non-technical multi-functional teams, with a sense of ownership for projects.

Technology stack

• PyTorch
• TensorFlow

Education and experience

• PhD in Computer Science or related field.

Preferred qualifications

• Experience in the advertising industry.
• Experience with distributed training and/or optimizing large-scale models for low-latency serving.
• Experience building infrastructure for 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.
• Advanced degree alignment options: 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.

Compensation and benefits

• Salary: USD 184,700 - 277,600 per year. Base pay depends on skills, qualifications, experience, and location.
• Equity: eligible to participate in Apple’s discretionary employee stock programs and become an Apple shareholder, with discretionary restricted stock unit awards (if eligible) and participation in the Employee Stock Purchase Plan to purchase Apple stock at a discount if voluntarily participating.
• Bonuses and relocation: role may be eligible for discretionary bonuses or commission payments as well as relocation (if eligible).
• Medical and wellness: comprehensive medical and dental coverage.
• Retirement: retirement benefits.
• Perks: a range of discounted products and free services.
• Education reimbursement: reimbursement for certain educational expenses, including tuition.
• Note: benefit, compensation, and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.