About the role
AI summarisedApple is seeking a Senior Machine Learning Engineer to develop advanced predictive models and AI-driven personalization systems using large-scale customer, market, and sales data. The role involves deploying models to generate business insights, building real-time personalization pipelines, and collaborating with cross-functional teams to turn prototypes into production systems. The engineer will work on cutting-edge techniques including Generative AI, Causal Inference, GNNs, and multi-modal LLMs to enhance user experiences globally.
TechnologyOnsiteMachine Learning and AI
Key Responsibilities
- Deploy predictive models to generate actionable insights for business strategy and decision-making
- Develop AI-driven personalization that provides 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
- 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 deploy 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
- Perform ongoing data analysis to build new or fine-tune existing models to optimize results
- Partner closely with software engineers to implement models into high-performing systems in the production environment for worldwide audience
- Actively engage in all aspects of model development, from ideation, experimentation, triaging to deployment
Requirements
- 5+ years of professional experience in building and deploying predictive models and AI-driven personalization at scale
- Ph.D. in Computer Science, Artificial Intelligence, Machine Learning or related field
- M.S. in related field with 3+ years experience applying machine learning to real business problems
- Proven expertise in data preprocessing, feature engineering, and analyzing large datasets to extract meaningful patterns
- Strong knowledge of state-of-the-art ML algorithms, including Generative AI and 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
- Excellent communication and soft skills
- Strong portfolio of shipped ML products, patents, or published research is a plus