Member of Technical Staff - Data Scientist (Machine Learning, Statistics)

Inflection AI is a public benefit corporation leveraging our world class large language model to build the first AI platform focused on the needs of the enterprise.

Who we are:

Inflection AI was re-founded in March of 2024 and our leadership team has assembled a team of kind, innovative, and collaborative individuals focused on building enterprise AI solutions. We are an organization passionate about what we are building, enjoy working together and strive to hire people with diverse backgrounds and experience.

Our first product, Pi, provides an empathetic and conversational chatbot. Pi is a public instance of building from our 350B+ frontier model with our sophisticated fine-tuning (10M+ examples), inference, and orchestration platform. We are now focusing on building new systems that directly support the needs of enterprise customers using this same approach.

Want to work with us? Have questions? Learn more below.

The Role

As a Member of Technical Staff - Data Scientist (Machine Learning, Statistics), you’ll be one of the first hires focused on building the experimentation and evaluation framework for our new enterprise ML product.

This role is core to defining how we measure success: from pre-deployment testing to live user impact analysis. As a Data Scientist, you’ll bring statistical rigor and clarity to noisy real-world data and help establish how we track quality, safety, and performance.

What You’ll Do

• Design and run experiments to measure model behavior, user experience, and product quality


• Define and track key performance metrics to guide iteration and inform strategic decisions


• Work with ML researchers to evaluate fine-tuning and training results using robust statistical methods


• Build dashboards and tools to monitor product and model performance over time


• Help define benchmarks and evaluation standards across the organization


• Design simple, intuitive UIs for non-technical users to explore and act on complex data


• Create interactive visualizations that reveal key patterns from high-dimensional datasets

You Might Be a Great Fit If You

• Have deep experience in applied statistics, experimentation design, and analysis


• Have built or contributed to evaluation systems for ML, with emphasis on safety, quality, or real-world impact


• Are confident designing and interpreting A/B, multivariate, and sequential experiments


• Can write data pipelines in Python using tools like pandas, NumPy, and statsmodels


• Want to shape foundational processes for evaluating large-scale machine learning systems