Apple Inc.
WW CSO - Machine Learning Engineer, Data Modeling
Apple Inc., Cupertino, California, United States, 95014
WW CSO - Machine Learning Engineer, Data Modeling
Cupertino, California, United States | Machine Learning and AI Description
In this role, you will focus on: Deploying predictive models to generate actionable insights for business strategy and decision-making. Developing AI-driven personalization that provides tailored suggestions based on customer behavior, preferences, and historical data. Leveraging user segmentation and clustering to enhance personalization precision for different customer groups. Experimenting with multi-modal data (text, images, customer interactions) to improve personalization. Implementing hybrid personalization models (Collaborative Filtering, Content-Based, Knowledge Graphs) to optimize user experiences. Building real-time personalization pipelines that dynamically adjust based on live user interactions. Leading exploration in predictive modeling of Large Language Models, Generative AI, Causal Inference Models, and GNNs, venturing into new areas. Turning prototypes into automated pipelines and deploying them into production, deciding when to use out-of-the-box vs. custom or hybrid solutions. Analyzing and preprocessing large-scale datasets to extract meaningful patterns and ensure model accuracy. Continuously analyzing data to build or fine-tune models for optimal results. Partnering closely with software engineers to implement models into high-performing production systems that enhance user experience. Engaging in all aspects of model development—from ideation and experimentation to deployment. Communicating results and insights effectively with partners. Maintaining expertise in the latest AI advancements and contributing to presentations, papers, and patents. Minimum Qualifications
5+ years of experience in building and deploying predictive models and AI-driven personalization at scale. Proven skills in data preprocessing, feature engineering, and analyzing large datasets. Strong knowledge of innovative ML algorithms, including Generative AI and Multi-modal LLMs. Understanding of insight modeling techniques such as Causal Inference, GNNs, and Forecasting. Hands-on experience with forecasting models, anomaly detection, and AI personalization methods. Proficiency in Python and ML frameworks like TensorFlow, PyTorch, Keras, scikit-learn. Experience with Big Data tools (SQL, Spark, Hadoop) and cloud-based ML pipelines. Track record of deploying ML models into production with performance optimization. Ph.D. in Computer Science, AI, or ML, or M.S. with 3+ years of relevant experience. Preferred Qualifications
Excellent communication and soft skills. Strong portfolio of shipped ML products, patents, or published research is a plus. Note: Compensation includes base pay ranging from $181,100 to $272,100, with potential for bonuses, stock options, and other benefits. Apple is an equal opportunity employer committed to diversity and inclusion.
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Cupertino, California, United States | Machine Learning and AI Description
In this role, you will focus on: Deploying predictive models to generate actionable insights for business strategy and decision-making. Developing AI-driven personalization that provides tailored suggestions based on customer behavior, preferences, and historical data. Leveraging user segmentation and clustering to enhance personalization precision for different customer groups. Experimenting with multi-modal data (text, images, customer interactions) to improve personalization. Implementing hybrid personalization models (Collaborative Filtering, Content-Based, Knowledge Graphs) to optimize user experiences. Building real-time personalization pipelines that dynamically adjust based on live user interactions. Leading exploration in predictive modeling of Large Language Models, Generative AI, Causal Inference Models, and GNNs, venturing into new areas. Turning prototypes into automated pipelines and deploying them into production, deciding when to use out-of-the-box vs. custom or hybrid solutions. Analyzing and preprocessing large-scale datasets to extract meaningful patterns and ensure model accuracy. Continuously analyzing data to build or fine-tune models for optimal results. Partnering closely with software engineers to implement models into high-performing production systems that enhance user experience. Engaging in all aspects of model development—from ideation and experimentation to deployment. Communicating results and insights effectively with partners. Maintaining expertise in the latest AI advancements and contributing to presentations, papers, and patents. Minimum Qualifications
5+ years of experience in building and deploying predictive models and AI-driven personalization at scale. Proven skills in data preprocessing, feature engineering, and analyzing large datasets. Strong knowledge of innovative ML algorithms, including Generative AI and Multi-modal LLMs. Understanding of insight modeling techniques such as Causal Inference, GNNs, and Forecasting. Hands-on experience with forecasting models, anomaly detection, and AI personalization methods. Proficiency in Python and ML frameworks like TensorFlow, PyTorch, Keras, scikit-learn. Experience with Big Data tools (SQL, Spark, Hadoop) and cloud-based ML pipelines. Track record of deploying ML models into production with performance optimization. Ph.D. in Computer Science, AI, or ML, or M.S. with 3+ years of relevant experience. Preferred Qualifications
Excellent communication and soft skills. Strong portfolio of shipped ML products, patents, or published research is a plus. Note: Compensation includes base pay ranging from $181,100 to $272,100, with potential for bonuses, stock options, and other benefits. Apple is an equal opportunity employer committed to diversity and inclusion.
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