Principal Applied Scientist
Tasks
- Apply model governance and Responsible AI practices
- Build recommendation and personalization models
- Conduct online experimentation
- Create evaluation frameworks for conversational shopping
- Design machine learning models for product discovery and ranking
- Develop LLM based conversational shopping systems
- Ground responses on structured commerce data
- Implement retrieval-augmented generation
- Manage hallucination and stale data risks
- Mentor applied science team members
- Orchestrate LLM tools and workflows
- Partner with Product, Engineering, and Design teams
- Perform prompt engineering for shopping assistants
- Provide technical leadership and design reviews
- Run offline metrics evaluations
- Set quality standards
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | ARIMA | Anomaly Detection | Apache Spark | Azure Databricks | B testing | Classification | Clustering | Experimentation | Generative AI | Isolation forests | Language Models | Large Language Models | Machine Learning | Offline evaluation | Personalization | Prompt engineering | Python | R | Ranking Systems | Recommendation Systems | Regression Analysis | Responsible AI | Responsible Machine Learning | Retrieval-Augmented Generation | SQL | Series analysis | Time Series | Time Series Analysis | Tool orchestration
Education
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