Description

Description

We're is looking for a highly skilled and motivated Machine Learning Engineer to join our Predictions group. We build the core machine learning models that power ad predictions and monetization across Apple's App Store and News platforms. The ideal candidate will bring deep expertise in machine learning, information retrieval, and large-scale modeling, and will thrive in a fast-paced, privacy-first environment. You'll work at the intersection of applied ML, deep learning, and retrieval systems-developing models that predict user interaction, optimize marketplace outcomes, and scale across billions of queries. You'll also explore and operationalize emerging techniques in Large Language Models (LLMs), Reinforcement Learning, and representation learning to advance Apple's ad prediction systems.

Responsibilities

• Design and implement ML models to improve predictions of user interaction, click-through rate (CTR), and conversion rate (CVR)
• Develop and optimize retrieval algorithms, leveraging techniques from classical IR and modern deep learning
• Contribute to core modeling areas such as deep neural networks, contextual bandits, multi-task learning, and LLM-based ranking signals
• Work with large-scale, distributed datasets to identify new signals and improve model accuracy and robustness
• Collaborate with cross-functional teams across engineering, infrastructure, and product to scale models to production
• Participate in designing and running large-scale experiments to validate new model architectures and learning strategies

Minimum Qualifications

• 4+ years of experience applying machine learning and statistical modeling at scale, preferably in ad tech, recommender systems, or web-scale search/retrieval
• Deep experience with neural network architectures (e.g., Transformers, DNNs, RNNs) and training pipelines using TensorFlow, PyTorch
• Practical understanding of reinforcement learning, explore/exploit strategies, and bandit-based optimization
• Experience working with high-volume data pipelines, A/B testing infrastructure, and performance measurement at scale
• Proficient in Python and familiar with SQL, Scala, or Java for production environments
• Ability to translate abstract ideas into concrete, high-impact solutions
• Bachelor's, or equivalent experience, in Computer Science, Machine Learning, Artificial Intelligence, Information Retrieval, or a related field.

Preferred Qualifications

• MS or PhD, or equivalent experience, in Computer Science, Machine Learning, Artificial Intelligence, Information Retrieval, or a related field.
• Great foundation in information retrieval, including query-document matching, embedding-based ranking, and learning-to-rank algorithms is a plus

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 $147,400 and $272,100, 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 .