资深软件开发工程师，研究系统工程
Staff+ Software Engineer, Research Systems Engineering
关于人类人文组织的使命是创建可靠，可解释和可引导的 AI 系统。我们希望人工智能对我们的用户以及整个社会来说都是安全和有益的。我们的团队是一个快速增长的致力于研究人员，工程师，政策专家和商业领导者组成的团队，共同努力建立有效的 AI 系统。有关 Anthropic 基础设施组织构建并运营分布式系统的角色，培训，服务和确保我们的 AI 模型。安тропо克的所有其他团队都依赖这些系统。在这个角色中，你将直接与我们的研究团队合作，以建设可靠，扩展性，性能高的基础设施我们的研究取决于。这是一个跨功能系统团队：你将制定和领导复杂的多个月基础设施项目，并解决我们能够增长速度限制的性能和可扩展性瓶。主要责任 ·独立实施和领导复合的多个个月基础架构项目，从一个模糊的起点到生产系统 ·与研究人员和研究团队建立深厚的合作伙伴关系以了解他们的需求并为他们提供服务 · 辅导其他工程师并帮助提高团队的技术标准 · 在多个团队之间建立技术方向上的协调，通过模糊的问题空间工作 ·随着使用和复杂性不断增长，你构建的系统可靠性，扩展性和安全性的责任· 领导基础设施中的运营流程改进，例如事件响应，死后检测和调用轮换，以便团队从每个事件中学习最低资格 · 在生产中设计，建造和操作大型分布式系统或基础设施的经验 · 自主地进行范围分析和执行复杂，模糊且多个月的技术项目 · 以其他工程师为导演或辅导员的先前经验 · 经历其他工程师和团队建立在其他工程师的建筑决策上 · 强大的软件工程基础知识和至少有一种编程语言的熟练能力 （例如 Python,Rust,Go,Java）·与现代云基础设施 （如 Kubernetes,基础设施作为代码，AWS,GCP）的经验 · 具有经验在多个团队或利益相关者之间建立协调力的书面和口头沟通技能；优先资格 ·不包括实习的10年以上软件工程经验 · 与 m 合作经验
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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
Anthropic's Infrastructure organization builds and operates the distributed systems that train, serve, and secure our AI models. Every other team at Anthropic depends on these systems.
In this role, you'll work directly with our Research teams to build the reliable, scalable, performant infrastructure our research depends on. This is a cross-functional systems team: you'll scope and lead complex, multi-month infrastructure projects and resolve the performance and scalability bottlenecks that limit how fast we can grow.
Key responsibilities
- Independently scope and lead complex, multi-month infrastructure projects, from an ambiguous starting point through to a production system
- Build deep partnerships with researchers and Research teams to understand their needs and deliver for them
- Mentor other engineers and help raise the technical bar for the team
- Build alignment on technical direction across multiple teams, working through ambiguous problem spaces
- Take ownership of the reliability, scalability, and security of the systems you build as usage and complexity grow
- Lead the improvement of operational processes across Infrastructure, such as incident response, postmortems, and on-call rotations, so the team learns from every incident
Minimum qualifications
- Experience designing, building, and operating large-scale distributed systems or infrastructure in production
- Experience independently scoping and delivering complex, ambiguous, multi-month technical projects
- Prior experience as a technical lead or mentor for other engineers
- Experience making architectural decisions that other engineers and teams build on top of
- Strong software engineering fundamentals and proficiency in at least one programming language (e.g., Python, Rust, Go, Java)
- Experience with modern cloud infrastructure (e.g., Kubernetes, infrastructure as code, AWS, GCP)
- Strong written and verbal communication skills, with experience building alignment across multiple teams or stakeholders
Preferred qualifications
- 10+ years of software engineering experience, not including internships
- Experience with machine learning infrastructure (e.g., GPUs, TPUs, Trainium) and associated networking infrastructure (e.g., NCCL)
- Low-level systems experience (e.g., Linux kernel tuning, eBPF)
- Experience applying security or privacy engineering best practices
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—$485,000 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.