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обновлено 27 дней назад

Research Scientist (AI)

216 000 - 270 000$
Тип работы
fulltime
Грейд
senior
Английский
c1
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR
Research Scientist (AI): Developing and applying post-training methods and interpretability techniques to enhance the safety and robustness of frontier AI systems with an accent on RLHF, DPO, and GRPO methodologies. Focus on designing post-training pipelines, conducting interpretability-informed evaluations, and translating research findings into actionable safety standards for industry and policymakers.

Salary: $216,000–$270,000 USD per year, with potential equity and benefits.

Company

Scale AI develops data, evaluation, and full-stack technologies that support reliable AI systems and help organizations build, deploy, and oversee AI applications.

What you will do

  • Design and run post-training pipelines to study how training choices affect model safety, robustness, and alignment.
  • Develop interpretability-informed evaluations for unsafe, deceptive, and otherwise undesirable model behaviors.
  • Use evaluation and interpretability insights to guide targeted safety mitigations.
  • Collaborate with policymakers, engineers, and researchers to translate findings into safety standards, benchmarks, and best practices.

Requirements

  • Experience with post-training and reinforcement learning methods such as RLHF, DPO, GRPO, or similar approaches.
  • Published research in machine learning, particularly generative AI.
  • At least three years of experience solving sophisticated machine learning problems in research or product development.
  • Strong written and verbal communication skills for cross-functional collaboration.
  • Commitment to safe, secure, and trustworthy AI deployment.

Nice to have

  • Experience with mechanistic interpretability, probing, or other methods for understanding model internals.
  • Familiarity with red-teaming or adversarial evaluation of post-trained models.
  • Experience studying reward hacking, sycophancy, alignment faking, or other post-training failure modes.

Culture & Benefits

  • Work alongside industry, public-sector, and academic collaborators, with opportunities to publish research.
  • Comprehensive health, dental, and vision coverage.
  • Retirement benefits, learning and development stipend, and generous paid time off.
  • Potential commuter stipend and equity compensation for eligible roles.
  • Inclusive equal-opportunity workplace with reasonable accommodation support.

Hiring process

  • Research interviews assess practical machine learning prototyping and debugging skills, research concepts, and organizational alignment.
  • No LeetCode-style questions are used.
  • Applicants are reconsidered for the same role only after a 90-day waiting period.

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