- Страна
- США
- Зарплата
- 320 000 $ – 405 000 $
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Research Engineer, AI Observability
Исключительная вакансия в одной из самых влиятельных ИИ-компаний мира с очень высокой компенсацией, сильной командой и возможностью напрямую влиять на безопасность ИИ.
Сложность вакансии
Роль требует редкого сочетания навыков: глубокого понимания LLM (Claude), опыта разработки высоконагруженных систем обработки данных и продуктового мышления для создания внутренних инструментов. Высокая планка ожиданий соответствует уровню ведущей ИИ-лаборатории мира.
Анализ зарплаты
Предлагаемая зарплата ($320k–$405k) находится на верхнем пределе рынка даже для Сан-Франциско, значительно превышая средние показатели для Senior/Staff инженеров в обычных технологических компаниях.
Сопроводительное письмо
I am writing to express my strong interest in the Research Engineer, AI Observability position at Anthropic. With over five years of experience in software engineering and a deep focus on machine learning systems, I have consistently sought to build tools that make complex data actionable. My background in developing LLM-based applications and orchestration frameworks aligns perfectly with your mission to use Claude for monitoring and understanding massive datasets.
In my previous roles, I have bridged the gap between infrastructure and user-facing products, ensuring that internal tools are not only powerful but also intuitive for researchers. I am particularly drawn to Anthropic’s commitment to AI safety and interpretability. I am eager to apply my skills in context engineering and large-scale data processing to help scale human oversight and mitigate misuse in AI deployments.
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Присоединяйтесь к Anthropic, чтобы создавать инструменты мониторинга ИИ нового поколения и определять будущее безопасного машинного обучения.
Описание вакансии
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the Team
As AI training and deployments scale, the volume of data we need to monitor and understand is exploding. Our team uses Claude itself to make sense of this data. We own an integrated set of tools enabling Anthropic to ask open-ended questions, surface unexpected patterns, and maintain meaningful human oversight over massive datasets.
Our tools are widely adopted internally — powering ongoing enforcement, threat intelligence investigations, model audits, and more — and we’re looking for experienced engineers and researchers to both scale up existing applications and go zero-to-one on new ones.
About the Role
As a Research Engineer on our team, you'll design and build systems that let AI analyze large, unstructured datasets — think tens or hundreds of thousands of conversations or documents — and produce structured, trustworthy insights. You'll work across the full stack, from core analysis frameworks through user-facing apps and interfaces.
This is a high-leverage role. The tools you build will be used by dozens of researchers and investigators, and directly shape our ability to measure and mitigate both misuse and misalignment.
Responsibilities:
- Design and implement AI-based monitoring systems for AI training and deployment
- Extend and improve core frameworks for processing large volumes of unstructured text
- Partner with researchers and safety teams across Anthropic to understand their analytical needs and build solutions
- Develop agentic integrations that allow AI systems to autonomously investigate and act on analytical findings
- Contribute to the strategic direction of the team, including decisions about what to build, what to partner on, and where to invest
You May Be a Good Fit If You:
- Have 5+ years of software engineering experience, with meaningful exposure to ML systems
- Are excited about the problem of scaling human oversight of AI systems
- Are familiar with LLM application development (context engineering, evaluation, orchestration)
- Enjoy building tools that other people use — you care about UX, reliability, and documentation
- Can context-switch between deep infrastructure work and user-facing product thinking
- Thrive in collaborative, cross-functional environments
Strong Candidates May Also Have:
- Research experience in AI safety, alignment, or responsible deployment
- Practical experience with both data science and engineering, including developing and using large-scale data processing frameworks
- Experience with productionizing internal tools or building developer-facing platforms
- Background in building monitoring or observability systems
- Comfort with ambiguity — our team is small and growing, and you'll help define what we become
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary:
$320,000—$405,000 USD
Logistics
Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process
Создайте идеальное резюме с помощью ИИ-агента

Навыки
- Python
- Machine Learning
- LLM
- Data Science
- Observability
- Software Engineering
- Data Processing
- AI Safety
Возможные вопросы на собеседовании
Проверка практического опыта работы с LLM и понимания ограничений контекстных окон.
Как бы вы спроектировали систему для анализа 100 000 диалогов с помощью Claude, учитывая ограничения по стоимости и размеру контекста?
Оценка навыков обеспечения надежности и точности ИИ-инструментов.
Как вы предлагаете оценивать 'доверенность' (trustworthiness) структурированных инсайтов, которые генерирует ваша система мониторинга?
Проверка способности работать на стыке инфраструктуры и продукта.
Опишите случай, когда вам пришлось балансировать между глубокой оптимизацией бэкенда и удобством интерфейса для конечного пользователя-исследователя.
Оценка понимания современных подходов к автономным агентам.
Какие основные риски вы видите в создании 'агентских интеграций' для автономного расследования аномалий в данных мониторинга?
Проверка соответствия миссии компании в области безопасности.
Как инструменты обсервабильности (observability) могут напрямую способствовать снижению рисков нецелевого использования (misuse) моделей?
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- Страна
- США
- Зарплата
- 320 000 $ – 405 000 $