Job Description

Locations

• Singapore, Singapore, Singapore 569141

Salary

Skills Required

• Machine Learningintermediate
• predictive modelingintermediate
• Generative AIintermediate
• Causal Inference Modelsintermediate
• AI-driven personalizationintermediate
• user segmentationintermediate
• clusteringintermediate
• multi-modal data analysisintermediate
• Collaborative Filteringintermediate
• Content-Based filteringintermediate
• Knowledge Graphsintermediate
• real-time personalization pipelinesintermediate
• Large Language Modelsintermediate
• GNNintermediate
• data preprocessingintermediate
• data analysisintermediate
• model deploymentintermediate
• production pipelinesintermediate
• stakeholder communicationintermediate
• collaborationintermediate
• innovationintermediate
• experimentationintermediate
• model fine-tuningintermediate

Required Qualifications

• 5+ years of professional experience in building and deploying predictive models and AI-driven personalization at scale. (experience, 5 years)
• Ph.D. in Computer Science, Artificial Intelligence, Machine Learning or related field; or (experience)
• M.S. in related field with 3+ years experience applying machine learning engineer to real business problems. (experience, 3 years)

Preferred Qualifications

• Proven expertise in data preprocessing, feature engineering, and analyzing large datasets to extract meaningful patterns. (experience)
• Strong knowledge of state-of-the-art ML algorithms, including Generative AI, Multi-modal LLMs. (experience)
• Solid understanding of insight modeling (Causal Inference Model, GNN, Generative AI, Forecasting). (experience)
• Hands-on experience in forecasting models, anomaly detection, and AI-driven personalization (matrix factorization, contextual recommendation, collaborative filtering). (experience)
• Proficiency in Python and key ML frameworks (TensorFlow, PyTorch, Keras, scikit-learn). (experience)
• Experience working with Big Data tools (SQL, Spark, Hadoop) and cloud-based ML pipelines. (experience)
• Track record of deploying ML models into production and optimizing for performance and scalability. (experience)
• Excellent communication and soft skills. (experience)
• Strong portfolio of shipped ML products, patents, or published research is a plus. (experience)

Responsibilities

• In this role, you will collaborate with a multidisciplinary team of ML engineers, data scientists, software engineers, researchers, designers and business partners to design, build, and deploy high-impact models.
• 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 stakeholders.
• - Maintain expertise in the latest advancements in AI technology. Partnering with your team members to prepare presentations, papers, and patents for your inventions.

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