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Оценка от Hirify AI
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Текст:
Hirify AI/Оригинал
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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