- Страна
- США
- Зарплата
- 500 000 $ – 850 000 $
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на вакансии с ИИ

Research Engineer, Virtual Collaborator (Cowork)
Это одна из самых престижных позиций в индустрии AI с чрезвычайно высокой компенсацией и возможностью работать в ведущей лаборатории мира. Роль предлагает уникальное сочетание фундаментальных исследований и прямого влияния на продукт Claude.
Сложность вакансии
Роль требует исключительного сочетания глубоких знаний в области обучения с подкреплением (RL) и сильных навыков продуктовой разработки. Кандидату необходимо иметь 5-8 лет опыта в ML и уметь работать в условиях высокой неопределенности, создавая системы оценки для открытых задач.
Анализ зарплаты
Предлагаемая зарплата ($500k - $850k) значительно превышает средние рыночные показатели даже для Senior/Staff уровней в топовых технологических компаниях США. Это ставит позицию в верхний 1% рынка труда в сфере AI.
Сопроводительное письмо
I am writing to express my strong interest in the Research Engineer position for Virtual Collaborator workflows at Anthropic. With over 7 years of experience in machine learning and a deep focus on reinforcement learning, I have consistently worked at the intersection of research and product, developing systems that are both technically rigorous and practically impactful. My background in building scalable RL environments and human-in-the-loop training systems aligns perfectly with your mission to make Claude the ultimate virtual collaborator for complex organizational tasks.
In my previous roles, I have specialized in creating robust evaluation frameworks and reward models that prevent reward hacking, particularly when dealing with open-ended tasks and enterprise data. I am particularly drawn to Anthropic's approach to AI as an empirical science and your commitment to building steerable, trustworthy systems. I am excited by the prospect of partnering with your product teams to transform Claude into a tool that can seamlessly navigate internal knowledge and co-create sophisticated documents, ultimately making AI a more helpful partner in everyday professional workflows.
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Откликнитесь в anthropic уже сейчас
Присоединяйтесь к Anthropic, чтобы обучать Claude работе с реальными бизнес-задачами и определять будущее виртуальных помощников.
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 role
We are looking for a Research Engineer to help us train Claude specifically for virtual collaborator workflows. While Claude excels at general tasks, a lot of knowledge work requires targeted training on real organizational data and workflows. Your job will be to design and implement reinforcement learning (RL) environments that transform Claude into the best virtual collaborator, training on realistic tasks from navigating internal knowledge to creating financial models.
Responsibilities:
- Training Claude on document manipulation with good taste, including understanding, enhancing, and co-creating (e.g., Office doc formats, data visualization)
- Designing and implementing reinforcement learning pipelines targeted at virtual collaborator use cases (productivity, organizational navigation, vertical domains)
- Building and scaling our data creation platform for generating high-quality, open-ended tasks with domain experts and crowdworkers Integrating real organizational data to create realistic training environments
- Developing robust evaluation systems that maintain quality while avoiding reward hacking
- Partnering directly with product teams (e.g., Cowork, claude.ai) to ensure training aligns with product features
You may be a good fit if you:
- Are a very experienced Python programmer who can quickly produce reliable, high quality code that your teammates love using
- Have 5-8 years of strong machine learning experience
- Thrive at the intersection of research and product, with a pragmatic approach to solving real-world problems
- Are comfortable with ambiguity and can balance research rigor with shipping deadlines
- Enjoy collaborating across multiple teams (data operations, model training, product)
- Can context-switch between research problems and product engineering tasks
- Care about making AI genuinely helpful for everyday enterprise workflows
Strong candidates may also have experience with:
- Creating RL envs for realistic tasks.
- Reward modeling and preventing reward hacking
- Building human-in-the-loop training systems or crowdsourcing platforms
- Working with enterprise tools and APIs (Google Workspace, Microsoft Office, Slack, etc.)
- Developing evaluation frameworks for open-ended tasks
- Domain expertise in finance, legal, or healthcare workflows
- Creating scalable data pipelines with quality control mechanisms
- Translating product requirements into technical training objectives
Deadline to apply:None. Applications will be reviewed on a rolling basis.
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:
$500,000—$850,000 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
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Навыки
- Python
- Machine Learning
- Data Visualization
- API
- Data Pipelines
- Reinforcement Learning
- Evaluation Frameworks
- Reward Modeling
Возможные вопросы на собеседовании
Проверка опыта в основной области ответственности — создании сред для обучения агентов.
Опишите ваш опыт проектирования RL-сред для решения сложных, многоэтапных задач. С какими основными трудностями вы столкнулись при моделировании реальности?
Критически важный навык для безопасности и надежности моделей Anthropic.
Как вы подходите к проблеме 'reward hacking' (взлома вознаграждения)? Приведите пример, когда агент нашел нежелательное решение, и как вы изменили функцию вознаграждения.
Вакансия подразумевает работу с офисными инструментами и данными.
Какие стратегии вы бы использовали для обучения модели манипулированию сложными форматами документов (например, Excel или PDF) при ограниченном объеме качественных данных?
Проверка способности работать на стыке науки и продукта.
Как вы балансируете между исследовательской строгостью и необходимостью быстро выпускать продуктовые фичи в условиях сжатых сроков?
Оценка навыков работы с данными и экспертами.
Расскажите о вашем опыте построения систем 'human-in-the-loop'. Как вы обеспечиваете качество данных, поступающих от краудворкеров или экспертов?
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- Страна
- США
- Зарплата
- 500 000 $ – 850 000 $