Senior-Staff Data Scientist (LLM)

About the Role

This role is for a senior individual contributor who will lead the design and improvement of LLM-powered solutions in a production environment. You will work on complex user-facing AI systems, drive experimentation and model improvement, and collaborate closely with cross-functional teams to turn ambiguous problems into practical, scalable solutions.

Responsibilities

• Lead the development and enhancement of LLM-based solutions for complex, real-world use cases
• Translate open-ended product or user problems into clear data science approaches, experiments, and deliverable outcomes
• Design, test, and refine prompts, retrieval strategies, evaluation frameworks, and model behaviors to improve quality and reliability
• Build robust experimentation methods to assess model performance and compare alternative approaches
• Work closely with product, engineering, analytics, and other technical teams to define priorities and drive implementation
• Take ownership of solution quality across the lifecycle, from early exploration through deployment and iteration
• Use data-driven methods to identify opportunities for model improvement, user impact, and system optimization
• Contribute to the design of scalable AI workflows, including evaluation pipelines, monitoring approaches, and feedback loops
• Help define best practices for production-grade LLM development, experimentation, and operational performance
• Communicate findings, trade-offs, and recommendations clearly to both technical and non-technical stakeholders
• Support strategic decisions on model quality, scalability, performance, and long-term maintainability
• Provide senior-level guidance in solving ambiguous AI problems with practical and measurable outcomes

Qualifications

• Proven experience in a Senior Data Scientist, Applied Scientist, ML Engineer, or similar role, with strong ownership of end-to-end ML or LLM initiatives
• Strong hands-on experience with LLMs in production settings, including experimentation, evaluation, iteration, and quality improvement
• Solid background in machine learning, statistics, and data science fundamentals
• Experience applying quantitative methods to solve complex product or system problems at scale
• Strong coding ability and practical experience working closely with software engineering teams in production environments
• Experience building or improving systems that involve prompt design, retrieval, ranking, response quality assessment, or model evaluation
• Strong understanding of experimentation design, success metrics, offline and online evaluation, and performance analysis
• Comfortable working with ambiguity and shaping loosely defined problems into structured analytical approaches
• Able to communicate complex technical ideas clearly and influence cross-functional stakeholders
• Experience operating in fast-paced, product-driven environments with high expectations for quality and execution
• Advanced degree in a relevant field such as Computer Science, Machine Learning, Statistics, Mathematics, Engineering, or a related quantitative discipline is preferred