Frontier AI Research Scientist - Benchmarks & Data

Cerebras; United States; On-site; USD 250,000 - 400,000; Full time

Job summary

Turing seeks exceptional AI Research Scientists to advance frontier AI evaluation and data generation. You will identify gaps, design benchmarks across STEM, and develop evaluation pipelines to improve model reliability and scientific capability.

This role emphasizes research leadership, rigorous experimentation, and collaboration across teams in a fast-moving environment. Office presence is required five days a week at SF, Palo Alto, or Seattle.

Qualifications

• PhD or equivalent research experience in machine learning, computer science, mathematics, physics, chemistry, biology, engineering, statistics, or another highly technical field.
• Demonstrated ability to formulate and execute original research.
• Strong understanding of modern LLMs and the frontier AI research landscape.
• Excellent experimental design, quantitative reasoning, and scientific judgment.
• Ability to rapidly understand unfamiliar technical literature and develop expertise in new areas.
• Strong Python skills and the ability to independently build research prototypes and evaluation pipelines.
• Excellent technical writing and communication.
• Comfort working in a fast-moving environment where the research agenda evolves with the frontier.

Responsibilities

• Identify high-impact gaps in existing benchmark and evaluation literature.
• Design novel benchmarks in and across STEM fields and on general model functionality.
• Develop evaluations for emerging model capabilities that are poorly captured by traditional static benchmarks.
• Design rigorous task-generation, grading, contamination-control, difficulty-calibration, and validation methodologies.
• Build benchmarks that can become both valuable research contributions and meaningful standards for evaluating frontier models.
• Develop methods for generating high-quality synthetic STEM training data.
• Study how task selection, difficulty, diversity, verification, filtering, and data quality affect downstream performance.
• Explore methods for generating useful training signal in domains where expert human data is scarce or expensive.
• Design experiments that determine when synthetic data genuinely improves capabilities rather than simply increasing training volume.
• Study hallucination, uncertainty, calibration, and epistemic failure in technical domains.
• Develop evaluations and methods for improving factual reliability, self-correction, verification, citation, and appropriate abstention.
• Investigate when models should reason internally, invoke tools, seek external evidence, or recognize that they do not know.
• Research AI systems capable of performing extended scientific and technical work.
• Develop workflows involving literature search, coding, simulation, tool use, experimentation, verification, and iterative reasoning.
• Evaluate long-horizon scientific agents and identify bottlenecks preventing them from reliably performing real research.
• Explore new approaches to human-AI and multi-agent scientific collaboration.

Skills

Python

LLMs

Research prototyping

Education

PhD or equivalent research experience

Job description

Turing seeks exceptional AI Research Scientists to advance frontier AI evaluation and data generation. You will identify gaps, design benchmarks across STEM, and develop evaluation pipelines to improve model reliability and scientific capability.

This role emphasizes research leadership, rigorous experimentation, and collaboration across teams in a fast-moving environment. Office presence is required five days a week at SF, Palo Alto, or Seattle.