Senior ML Engineer - Search & Recommendation Systems

Apple Inc.; Cupertino (CA); On-site; USD 175,000 - 313,000; Full time

Job summary

A leading company in Cupertino is seeking a Senior ML Engineer to enhance their Search and Recommendation Systems. The ideal candidate will have extensive experience in machine learning, particularly in recommendation systems, and will thrive in a collaborative environment. Responsibilities include designing algorithms, optimizing search relevance, and working with cross-functional teams to align features with business goals.

Benefits

Comprehensive medical and dental coverage

Retirement benefits

Discounted products and free services

Tuition reimbursement

Discretionary bonuses

Qualifications

• 10+ years of experience in Machine Learning or Data Science.
• Experience building large-scale Recommendation or Search systems.

Responsibilities

• Designing recommendation algorithms and search systems.
• Driving end-to-end machine learning workflows.

Skills

Python

Scala

Java

Machine Learning

Data Science

Software Engineering

Education

BS in Computer Science

MS in Computer Science

Tools

TensorFlow

PyTorch

XGBoost

Spark

Flink

Job description

Cupertino, California, United States Software and Services

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Description

This role is ideal for a technically deep individual who thrives in a fast-paced environment, has a strong product sense, and enjoys solving real-world problems using modern and novel AI models and scalable systems. We are passionate team of hardworking engineers, researchers, and scientists with common goals in mind, and we are looking for a strong Search and Recommendations Machine Learning engineer to join our team and be a part of the next revolution in human-computer interaction!KEY RESPONSIBILITIES INCLUDE BUT ARE NOT LIMITED TO:- Designing and implementing recommendation algorithms including collaborative filtering, content-based filtering, deep learning models (e.g., DLRM, transformers), and hybrid systems.- Developing personalized search and retrieval systems, optimizing ranking and relevance through ML/AI models and heuristics.- Driving end-to-end machine learning workflows — from data ingestion and preprocessing to model training, deployment, and monitoring in production.- Collaborating with cross-functional teams including Research Scientists, Product, Data Engineering, Search Infra teams, and UX to align recommendations/search features with business and user goals.- Defining and implementing offline and online evaluation metrics, A/B testing frameworks, and continuous improvement strategies.- Staying up to date with the latest research and innovations in recommendation systems and search-related ML technologies, and translating them into scalable production systems.

Minimum Qualifications

• 10+ years of experience in Machine Learning, Data Science, or Software Engineering roles with a significant focus on recommendation systems and/or search infrastructure.
• Validated experience building and deploying large-scale Recommendation or Search systems in production.
• Strong proficiency in Python, Scala, or Java or other generalist programming languages
• Deep familiarity with ML frameworks (TensorFlow, PyTorch, XGBoost, etc.).
• Solid understanding of ML system design, model lifecycle, and experimentation pipelines.
• Extensive experience working with large datasets, data processing pipelines (e.g., Spark, Flink), and scalable architectures.
• Deep understanding of information retrieval, ranking algorithms, and user modeling techniques.
• Experience with real-time systems, user feedback loops, and model retraining pipelines.
• BS or MS in Computer Science, Machine Learning, Statistics, or a related field.

Preferred Qualifications

• PhD Preferred
• Published work or patents in the domain of search/recommendation systems or related ML fields.
• Experience with modern vector search and retrieval techniques
• Strong foundation in deep learning architectures for personalization (e.g., transformers, graph neural networks, multi-task learning).
• Exposure to multi-objective optimization in recommender systems (e.g., engagement, diversity, novelty, fairness).
• Familiarity with MLOps tools and cloud platforms (AWS/GCP/Azure, Kubeflow, MLFlow, etc.).

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 $175,800 and $312,200, 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 .

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