About Turing
Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L
Role Overview
We are looking for experienced Data Analysts (MLE Bench) to contribute to benchmark-driven evaluation projects focused on real-world machine learning systems. This role involves hands-on analytical work with production-like datasets, metrics, and ML outputs to help evaluate, diagnose, and improve the performance of advanced AI systems.
The ideal candidate is comfortable working at the intersection of data analysis and machine learning, with strong analytical rigor and the ability to work with real datasets and ML evaluation workflows.
What does day-to-day life look like?
- Analyze structured and unstructured datasets generated from ML training, inference, and evaluation pipelines.
- Define, compute, and validate metrics used to evaluate model performance and behavior.
- Investigate data distributions, model outputs, failure modes, and edge cases relevant to benchmark tasks.
- Write and run Python and SQL code to analyze data, create reports, and support evaluation workflows.
- Validate data quality, consistency, and correctness across datasets and experiments.
- Create clear, well-documented analytical artifacts and reproducible analysis workflows.
- Collaborate with ML engineers and researchers to design challenging, real-world evaluation scenarios for MLE Bench.