Developing next-generation language model technology for enterprise applications and building responsible, high-impact solutions for real-world business challenges
Requirements
- Advanced degree in Statistics, Data Science, or related technical field (or equivalent hands-on experience)
- Strong background in applied statistics and experimental design
- Expertise in Python and libraries such as pandas, NumPy, and statsmodels
- Experience designing and analyzing experiments for machine learning systems
- Experience developing ML evaluation or observability tools in a production environment
- Familiarity with model safety, alignment, or real-world quality frameworks
Responsibilities
- Design and execute A/B, multivariate, and sequential experiments to evaluate model behavior and user impact
- Develop and monitor KPIs that inform product direction and model development
- Collaborate with ML researchers to assess training outcomes using rigorous statistical methods
- Build reliable data pipelines and tooling for tracking performance, leveraging Python and scientific computing libraries
- Create dashboards and interactive UIs to help non-technical stakeholders explore key insights
- Establish benchmark standards and evaluation protocols for internal use
- Visualize patterns in high-dimensional datasets to drive model alignment and product quality
Other
- Applicants must be currently authorized to work in the United States on a full-time basis now and in the future
- Advanced degree in Statistics, Data Science, or related technical field (or equivalent hands-on experience)
