研究工程师/研究科学家,预训练
Research Engineer/Research Scientist, Pre-training
关于Anthropic
Anthropic的使命是创造可靠、可解释且可引导的人工智能系统。我们希望人工智能对我们的用户以及整个社会都是安全且有益的。我们的团队是一个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群体,共同致力于构建有益的人工智能系统。
Anthropic处于人工智能研究的最前沿,致力于开发安全、符合伦理且强大的人工智能。我们的使命是确保变革性人工智能系统与人类利益保持一致。我们正在寻找一名研究工程师加入我们的预训练团队,负责开发下一代大型语言模型。在此职位中,您将在尖端研究与实际工程的交汇处工作,为开发安全、可引导且值得信赖的人工智能系统做出贡献。
主要职责:
- 在模型架构、算法、数据处理和优化器开发等领域进行研究并实现解决方案
- 独立领导小型研究项目,同时与团队成员合作开展更大的项目
- 设计、运行和分析科学实验,以加深我们对大型语言模型的理解
- 优化和扩展我们的训练基础设施,以提高效率和可靠性
- 开发和改进开发工具,以提高团队生产力
- 参与整个技术栈,从底层优化到高层模型设计
资格要求:
- 计算机科学、机器学习或相关领域的硕士或博士学位
- 强大的软件工程技能,有构建复杂系统的成功经验
- 精通Python,有使用深度学习框架的经验(PyTorch优先)
- 熟悉大规模机器学习,特别是在语言模型的背景下
- 能够在研究目标与实际工程约束之间取得平衡
- 强大的问题解决能力,结果导向的思维模式
- 优秀的沟通能力,能够在协作环境中工作
- 关注你工作的社会影响
优先考虑的经验:
- 参与高性能、大规模机器学习系统的工作
- 熟悉GPU、Kubernetes和操作系统内部
- 使用Transformer架构进行语言建模的经验
- 了解强化学习技术
- 具有大规模ETL流程的背景
如果你:
- 有丰富的软件工程经验
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.
Anthropic is at the forefront of AI research, dedicated to developing safe, ethical, and powerful artificial intelligence. Our mission is to ensure that transformative AI systems are aligned with human interests. We are seeking a Research Engineer to join our Pre-training team, responsible for developing the next generation of large language models. In this role, you will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems.
Key Responsibilities:
- Conduct research and implement solutions in areas such as model architecture, algorithms, data processing, and optimizer development
- Independently lead small research projects while collaborating with team members on larger initiatives
- Design, run, and analyze scientific experiments to advance our understanding of large language models
- Optimize and scale our training infrastructure to improve efficiency and reliability
- Develop and improve dev tooling to enhance team productivity
- Contribute to the entire stack, from low-level optimizations to high-level model design
Qualifications:
- Advanced degree (MS or PhD) in Computer Science, Machine Learning, or a related field
- Strong software engineering skills with a proven track record of building complex systems
- Expertise in Python and experience with deep learning frameworks (PyTorch preferred)
- Familiarity with large-scale machine learning, particularly in the context of language models
- Ability to balance research goals with practical engineering constraints
- Strong problem-solving skills and a results-oriented mindset
- Excellent communication skills and ability to work in a collaborative environment
- Care about the societal impacts of your work
Preferred Experience:
- Work on high-performance, large-scale ML systems
- Familiarity with GPUs, Kubernetes, and OS internals
- Experience with language modeling using transformer architectures
- Knowledge of reinforcement learning techniques
- Background in large-scale ETL processes
You'll thrive in this role if you:
- Have significant software engineering experience
- Are results-oriented with a bias towards flexibility and impact
- Willingly take on tasks outside your job description to support the team
- Enjoy pair programming and collaborative work
- Are eager to learn more about machine learning research
- Are enthusiastic to work at an organization that functions as a single, cohesive team pursuing large-scale AI research projects
- Are working to align state of the art models with human values and preferences, understand and interpret deep neural networks, or develop new models to support these areas of research
- View research and engineering as two sides of the same coin, and seek to understand all aspects of our research program as well as possible, to maximize the impact of your insights
- Have ambitious goals for AI safety and general progress in the next few years, and you’re working to create the best outcomes over the long-term.
Sample Projects:
- Optimizing the throughput of novel attention mechanisms
- Comparing compute efficiency of different Transformer variants
- Preparing large-scale datasets for efficient model consumption
- Scaling distributed training jobs to thousands of GPUs
- Designing fault tolerance strategies for our training infrastructure
- Creating interactive visualizations of model internals, such as attention patterns
At Anthropic, we are committed to fostering a diverse and inclusive workplace. We strongly encourage applications from candidates of all backgrounds, including those from underrepresented groups in tech.
If you're excited about pushing the boundaries of AI while prioritizing safety and ethics, we want to hear from you!
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.