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Описание вакансии
Текст:
TL;DR
Research Engineer, Takeoff Intel (AI evaluations): Building and running large-scale capability evaluations, measurement instruments, and data pipelines that turn model outputs and telemetry into reliable metrics with an accent on rapid prototyping, measurement accuracy, and AI-assisted research. Focus on designing LLM evaluation infrastructure, processing large volumes of data, validating experimental instruments, and translating research questions into actionable safety and situational-awareness measurements.
Location: Remote-friendly, San Francisco, United States; staff are expected to work from one of Anthropic's offices at least 25% of the time, with travel required.
Annual salary: $350,000–$850,000 USD
Company
Anthropic develops reliable, interpretable, and steerable AI systems focused on safety and societal benefit.
What you will do
- Design, build, and run capability evaluations and measurement instruments at scale.
- Develop data and analysis pipelines that convert model outputs and telemetry into reliable metrics.
- Prototype, validate, and refine new research instruments quickly.
- Review and supervise AI-written code as part of the engineering workflow.
- Collaborate with research scientists and partner teams to define meaningful measurements.
- Contribute to internal research write-ups and public reporting.
Requirements
- Bachelor's degree or an equivalent combination of education, training, and experience in a relevant field.
- Experience shipping an evaluation, data product, or research library end to end.
- Experience running experiments on large language models.
- Ability to prototype quickly, work with messy large-volume data, and operate from ambiguous research questions.
- Clear communication and close collaboration with research teams.
- Availability to work from an Anthropic office at least 25% of the time and travel as required.
Nice to have
- Experience building LLM evaluation harnesses or benchmark infrastructure.
- Large-scale ML or data infrastructure experience.
- Experience building tools or libraries used by other researchers.
- Experience identifying errors in AI-written code.
Culture & Benefits
- Collaborative research environment focused on high-impact AI safety and empirical science.
- Frequent research discussions and close collaboration across research, policy, economics, pretraining, and reinforcement learning teams.
- Flexible working hours and a collaborative office environment.
- Competitive compensation, equity donation matching, generous vacation, and parental leave.
- Visa sponsorship is available, subject to role and candidate eligibility.
Hiring process
- Applications are evaluated with consideration for equivalent education, training, and experience.
- Candidates may use AI in the application process according to Anthropic's candidate AI usage guidance.
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