Research Scientist, STEM
$150k - $300k • Remote • United States
Posted 22d ago
Remote Work Policy
Fully remote
Categories
AI Research Engineer
About the job
Turing is seeking exceptional AI Research Scientists to join our STEM research organization and develop new ways to evaluate, train, and improve frontier AI systems. This is a research-first role focused on problems where the right benchmark, dataset, or methodology often does not yet exist. You will identify important gaps in the literature, propose ambitious new research directions, and take projects from initial hypothesis through experimentation, benchmark construction, and publication. Our research is deliberately focused on frontier STEM evaluation, synthetic data, hallucination and reliability, and agentic science. We are looking for scientists who can recognize important problems early, formulate them precisely, and design rigorous research programs to answer them.
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 poorly captured by traditional static benchmarks.
- Design methodologies for task generation, grading, contamination control, difficulty calibration, and validation.
- Build benchmarks that serve as valuable research contributions and standards for evaluating frontier models.
- Develop methods for generating high-quality synthetic STEM training data.
- Study the impact of task selection, difficulty, diversity, verification, filtering, and data quality on downstream performance.
- Explore methods for generating useful training signals in domains with scarce or expensive human data.
- Design experiments to determine when synthetic data genuinely improves capabilities.
- 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 abstain.
- 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 reliable real research.
- Explore new approaches to human-AI and multi-agent scientific collaboration.
- Propose new research programs in areas such as reasoning, model evaluation, AI-for-science, data generation, and emerging capabilities.
Requirements
- 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 ability to independently build research prototypes and evaluation pipelines.
- Excellent technical writing and communication skills.
- Comfort working in a fast-moving environment where the research agenda evolves.
- Ability to identify important questions, design rigorous ways to answer them, and execute quickly.