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Apple Senior ML Engineer - Search & Recommendation Systems United States, California, Cupertino 443079927
Today
We are seeking a highly experienced and innovative Recommendation Systems Engineer to help design, develop, and optimize large-scale recommendation and search systems. You will work closely with other AI/ML Scientists and experts at the intersection of Generative AI and Information Retrieval, crafting intelligent systems that personalize user experiences.
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.- 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.
- 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.
- 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.).
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
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