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Senior Research Scientist, STEM

Training Superintelligence· R&D / Engineering
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Remote$250k - $350kFull-timePosted 3w ago

About the role

Research Scientist role focused on frontier STEM evaluation, synthetic data, hallucination and reliability, and agentic science to advance frontier AI systems through benchmarks, datasets, and methodologies.

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 reliable real research.
  • Explore new approaches to human-AI and multi-agent scientific collaboration.

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.

Skills

Required:PhD or equivalent research experience in a highly technical fieldOriginal research formulation and executionUnderstanding of modern LLMs and frontier AI landscapePythonTechnical writing and communication
Last updated Sep 30, 2026. Interested? Apply on the company site.

About Training Superintelligence

Turing develops large-scale RL environments and data generation systems that train multimodal agents to improve model performance in coding, real-world, economically valuable tasks, and advanced STEM reasoning.

Train AIBuild AIHire AI TalentAI for BFSIEMNAIDatasetsEnterprise Knowledge WorkMultimodal
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