WW CSO – Machine Learning Engineer, Data Modeling – Apple
Job Description
In this role, you will focus on the following key areas:- deploy predictive models to generate actionable insights for business strategy and decision-making.- Develop AI-driven personalization that provide tailored suggestions based on customer behavior, preferences, and historical data.- Leverage user segmentation and clustering to enhance personalization precision for different customer groups.- Experiment with multi-modal data (text, images, customer interactions) to improve personalization.- Implement hybrid personalization models (Collaborative Filtering, Content-Based, Knowledge Graphs) to optimize user experiences.- Build real-time personalization pipelines that can dynamically adjust based on live user interactions.- Lead the exploration for predictive modeling of Large Language Models and Generative AI, Causal Inference Model, GNN, venturing into new areas within these fields.- Turn prototypes into automated pipelines and deploying them to production; deciding when to use out-of-the-box solutions vs. building custom solutions or a hybrid approach.- Analyze and preprocess large scale datasets to extract meaningful patterns and ensure model accuracy- Ongoing data analysis to build new or fine-tune existing models to optimize results- Partner closely with software engineers to implement these models into high-performing systems and models in our production environment that can be applied to create amazing experience for our worldwide audience- Actively engaging in all aspects of model development, from ideation, experimentation, triaging to deployment.- Communicate results/reports with partners- Maintain expertise in the latest advancements in AI technology. Partnering with your team members to prepare presentations, papers, and patents for your inventions
- 5+ years of professional experience in building and deploying predictive models and AI-driven personalization at scale.
- Proven expertise in data preprocessing, feature engineering, and analyzing large datasets to extract meaningful patterns.
- Strong knowledge of innovative ML algorithms, including Generative AI, Multi-modal LLMs.
- Solid understanding of insight modeling (Causal Inference Model, GNN, Generative AI, Forecasting).
- Hands-on experience in forecasting models, anomaly detection, and AI-driven personalization (matrix factorization, contextual recommendation, collaborative filtering)
- Proficiency in Python and key ML frameworks (TensorFlow, PyTorch, Keras, scikit-learn).
- Experience working with Big Data tools (SQL, Spark, Hadoop) and cloud-based ML pipelines.
- Track record of deploying ML models into production and optimizing for performance and scalability.
- Ph.D. in Computer Science, Artificial Intelligence, Machine Learning or related field; or M.S. in related field with 3+ years experience applying machine learning engineer to real business problems
- Excellent communication and soft skills.
- Strong portfolio of shipped ML products, patents, or published research is a plus.
