About the position
As an AI Engineer & Researcher - Product Experimentation Design at xAI, you will be at the forefront of transforming user feedback and behavioral data into actionable insights that drive rapid product evolution. This role combines deep expertise in mathematics, statistics, and creative problem-solving to dissect complex, noisy signals from our AI systems—such as production logs, user interactions, and engagement metrics—without directly training models. You'll design clever experiments to test hypotheses, quantify what users love or loathe about our products, and recommend precise course corrections to enhance satisfaction and performance. By accelerating iteration cycles through smart experimentation, you'll empower our teams to make data-informed decisions that keep our AI at the cutting edge of user delight.
Responsibilities
- Dive into production logs and behavioral data to identify patterns of dissatisfaction, using mathematical and statistical tools to distill why users may not engage with or appreciate aspects of our AI models.
- Craft and execute fast-paced experiments, such as A/B tests or multivariate trials, to validate hypotheses on product features and measure their impact on user experience.
- Apply advanced stats and creative analytical techniques to interpret ambiguous data streams, uncovering hidden correlations and causal factors that inform product improvements.
- Synthesize findings into clear, evidence-based strategies for product decisions, prioritizing quick wins and long-term enhancements to boost model usability and appeal.
- Optimize experimentation pipelines for speed, enabling frequent testing and refinement cycles that allow the team to pivot based on real-time user signals and evolving needs.
Requirements
- Profound skills in math, probability, statistics, and inference, with a proven ability to apply them creatively to real-world problems in dynamic tech environments.
- Hands-on experience designing and analyzing product experiments (e.g., A/B testing, causal inference), with a track record of accelerating iteration in AI or software products.
- Demonstrated talent for teasing insights from noisy, high-volume data sources like logs and metrics, leading to innovative solutions that address user pain points without model training.
- Background in using data-driven methods to guide strategic choices, such as identifying suboptimal features and proposing fixes in fast-paced settings.
- 3+ years in AI engineering or research roles at innovative companies, where you've balanced technical rigor with creative thinking to deliver quick, impactful iterations.
