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:
- Data Infrastructure: We build and maintain the data systems powering Anthropic's AI research and products. You'll design and optimize data pipelines using tools like Spark, Airflow, and dbt across GCP and AWS. Your work will ensure reliable, scalable data infrastructure while implementing governance best practices and driving continuous improvement.
- Core Infrastructure: The systems team is responsible for supporting some of the largest, most sophisticated clusters in industry used to train, research, and ultimately serve AI models. Your work will be crucial in ensuring Anthropic is able to continue reliably and safely training frontier models. You will be responsible for building systems and running large Kubernetes clusters with GPU/TPU/Tranium workloads.
- Runtime Platform: We build and maintain the infrastructure that monitors the health, performance, and efficiency of our AI systems. You'll work across teams to implement monitoring solutions using tools like Prometheus, Splunk, and Grafana, while developing automated approaches for dashboards and alerts. Your work will create reliable, low-maintenance systems that enable proactive monitoring and operational excellence.
- Developer Productivity: The Developer Productivity team enables Anthropic researchers and engineers to be maximally effective in securely developing state-of-the-at models, and products that expose those models to users. All of the code written at Anthropic goes through systems/infrastructure built and maintained by our team. We aim to make development at Anthropic secure, efficient, and delightful.
- Product Infrastructure: The Product Infrastructure team enables Anthropic's products to achieve best-in-class performance, reliability, and developer velocity by building and maintaining a robust, efficient, and scalable product infrastructure stack.
- Cloud Inference: We scale and optimize Claude to serve the massive audiences of developers and enterprise companies using AWS and GCP. Our team's engineers are extremely high leverage because we simultaneously drive two of our company's largest and fastest growing revenue streams, and we optimize the consumption of one of our most precious resources: compute. Our team ensures our LLMs meet rigorous safety, performance, and security standards and enhance our core infrastructure for packaging, testing, and deploying inference technology. Your work will increase the scale at which our services can operate and accelerate our ability to reliably launch new frontier models and innovative features to customers across all platforms.
Responsibilities:
- Lead build out of industry-leading AI clusters (thousands to hundreds of thousands of machines), partnering closely with cloud service providers on cluster build out and required features
- Consult with different stakeholders to deeply understand infrastructure, data and compute needs, identifying potential solutions to support frontier research and product development
- Set technical strategy and oversee development of high scale, reliable infrastructure systems.
- Mentor top technical talent
- Design processes (e.g. postmortem review, incident response, on-call rotations) that help the team operate effectively and never fail the same way twice
You may be a good fit if you:
- Have 10+ years of relevant industry experience, 3+ years leading large scale, complex projects or teams as an engineer or tech lead
- Are obsessed with distributed systems at scale, infrastructure reliability, scalability, security, and continuous improvement
- Strong proficiency in at least one programming language (e.g., Python, Rust, Go, Java)
- Strong problem-solving skills and ability to work independently
- Have a passion for supporting internal partners like research to understand their needs
- Have excellent communication skills to build consensus with stakeholders, both internally and externally
- Possess deep knowledge of modern cloud infrastructure including Kubernetes, Infrastructure as Code, AWS, and GCP
Strong candidates may also:
- Have security and privacy best practice expertise
- Experience with machine learning infrastructure like GPUs, TPUs, or Trainium, as well as supporting networking infrastructure like NCCL
- Low level systems experience, for example linux kernel tuning and eBPF
- Technical expertise: Quickly understanding systems design tradeoffs, keeping track of rapidly evolving software systems
Deadline to apply: None. Applications will be reviewed on a rolling basis.
The expected salary range for this position is:
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.
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.
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