Principal Data Scientist (User Understanding Platformisation)
Tasks
- Advance generative recommendation using foundation models and unified user item representations
- Architect and develop large scale user understanding systems
- Define technical strategy and roadmap for user understanding and generative personalization
- Design production architectures for large scale model training and low latency serving
- Develop reusable user representations and foundation models
- Establish offline and online evaluation methodologies
- Evaluate research and transition prototypes into production
- Platformize user understanding by building reusable representations models features APIs and serving systems
Perks/Benefits
- Benefits package
- Birthday leave
- Flexible work hours
- Medical insurance
- Parental leave
- Term life insurance
- Volunteering leave
Skills/Tech-stack
A/B | A/B Testing | Apache Spark | B testing | Deep learning | Distributed Training | Embedding | Feature Engineering | Foundation Models | Generative Recommendation | Generative Retrieval | Information Retrieval | Language Processing | Machine Learning | Model Monitoring | Natural Language | Natural Language Processing | PyTorch | Python | Real Time | Real-time Inference | Recommendation Systems | Representation Learning | Scala | Sequence Modeling | TensorFlow | Transformers | User Modeling
Education
Master of Engineering | Master of Science | Master of Science in Artificial Intelligence | Master of Science in Computer Science | Master of Science in Machine Learning
Roles
Data Scientist | Principal | Principal Data Scientist | Scientist
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