远程工作雷达

研究工程师,知识团队

Research Engineer, Knowledge Team

AI开发工程全球可投
公司Anthropic
薪资未公开
工作地点Remote-Friendly (Travel-Required) | San Francisco, CA | Seattle, WA | New York City, NY
地域资格全球可投
时区要求无特别要求
用工类型未标注
发布时间2024-04-23
数据来源Greenhouse
前往企业招聘页投递 →
全球可投:该职位未限制候选人所在地区。仍需注意薪资可能按地区折算,以及实际签约方式(正式雇佣 / 独立合同)。

关于Anthropic

Anthropic的使命是创造可靠、可解释且可引导的AI系统。我们希望AI对我们的用户以及整个社会都是安全且有益的。我们的团队是一支快速发展的由致力于研究、工程、政策专家和商业领袖组成的团队,共同构建有益的AI系统。

关于该职位:

我们正在寻找研究工程师,帮助我们重新设计Claude与外部数据源的交互方式。许多关于数据和知识库组织的范式假设了人类消费者和限制条件。在LLM的世界中,这种情况已经不再成立!你的工作将是设计信息的新架构,并训练语言模型以最优方式使用这些架构。

职责:

  • 从零开始设计和实现新的信息架构策略
  • 执行微调和强化学习,教授语言模型如何与新的信息架构进行交互
  • 构建“硬”知识库评估集,以帮助识别语言模型处理外部数据时的故障模式
  • 设计和评估先进的代理搜索功能

你可能适合这个职位,如果你:

  • 是一位经验非常丰富的Python程序员,能够快速编写出队友喜爱使用的可靠高质量代码
  • 有良好的机器学习研究经验
  • 有开发利用大型语言模型(如Claude)的软件的经验
  • 以结果为导向,具有灵活性和影响力的倾向
  • 即使超出你的工作描述,也能主动补上空缺
  • 喜欢结对编程(我们非常喜欢结对!)
  • 想与世界级的ML研究人员合作,开发新的LLM能力
  • 关心你工作的社会影响
  • 有清晰的书面和口头沟通能力

优秀的候选人还具备以下经验:

  • 与产品团队合作,快速原型设计并交付创新解决方案
  • 构建复杂的代理系统,利用LLM
  • 开发可扩展的分布式信息检索系统,如搜索引擎、知识图谱、RAG、索引、排序、查询理解和分布式数据处理

该职位的年度薪酬范围如下。

对于销售职位,提供的范围是该职位的“目标收益”("OTE"),即该范围包括该职位的销售佣金/销售奖金目标和年度基本工资。

年度薪资:
350,000美元—

查看英文原文

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 Research Engineers to help us redesign how Claude interacts with external data sources. Many of the paradigms for how data and knowledge bases are organized assume human consumers and constraints. This is no longer true in a world of LLMs! Your job will be to design new architectures for how information is organized, and train language models to optimally use those architectures.

Responsibilities:

  • Designing and implementing from scratch new information architecture strategies
  • Performing finetuning and reinforcement learning to teach language models how to interact with new information architectures
  • Building “hard” knowledge base eval sets to help identify failure modes of how language models work with external data
  • Designing and evaluating advanced agentic search capabilities.

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 good machine learning research experience
  • Have experience developing software that utilizes Large Language Models such as Claude
  • Are results-oriented, with a bias towards flexibility and impact
  • Pick up slack, even if it goes outside your job description
  • Enjoy pair programming (we love to pair!)
  • Want to partner with world-class ML researchers to develop new LLM capabilities
  • Care about the societal impacts of your work
  • Have clear written and verbal communication

Strong candidates will also have experience with:

  • Collaborating with product teams to quickly prototype and deliver innovative solutions
  • Building complex agentic systems that utilize LLMs
  • Developing scalable distributed information retrieval systems, such as search engines, knowledge graphs, RAG, indexing, ranking, query understanding, and distributed data processing

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:
$350,000—$850,000 USD

Logistics

Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

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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