Who is our client?
Our client is a large-scale technology organization with a strong focus on engineering, data, and AI. They are continuing to invest in AI/ML platform capabilities that enable teams to build, operate, and scale machine learning and intelligent applications more effectively.
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.
*Relocation sponsorship is provided
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
