Principal Applied Scientist

What you'll do

• Design and build machine learning models for product discovery and personalization using large-scale commerce data.
• Develop conversational shopping systems with LLMs, focusing on prompt design and retrieval-augmented generation techniques.
• Address quality challenges in AI systems to ensure reliability and trustworthiness in user interactions.
• Define evaluation frameworks and conduct experiments for conversational and proactive shopping scenarios.
• Provide technical leadership by mentoring team members and setting quality standards for applied science projects.
• Contribute to model governance and Responsible AI practices to maintain system compliance and ethical use.

What we're looking for

• Extensive hands-on experience developing machine learning models for real-world applications.
• Proficiency in Python or R for data analysis and modeling, with knowledge of SQL.
• Experience with large-scale data processing using tools like Apache Spark or Azure Databricks.
• Expertise in time-series analysis and anomaly detection techniques for business insights.
• Practical experience with prompt engineering and fine-tuning LLMs for domain-specific applications.
• Ability to address quality and trust challenges in AI systems, including hallucination risk and recommendation reliability.