Staff + Sr. Software Engineer, Scaling

Anthropic

New York (NY)

Hybrid

USD 320,000 - 485,000

Full time

2 days ago
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Benefits offered by this job

Competitive compensation
Benefits package
Equity donation matching (optional)
Generous vacation and parental leave
Flexible working hours
Office space and collaboration areas

Job summary

Anthropic is seeking a senior software engineer for its Inference team in New York. You will design and operate distributed systems powering Claude at scale, with intelligent routing, auto-scaling, and deployment pipelines across multiple cloud providers.

The role emphasizes compute efficiency and collaboration with researchers and engineers, requiring strong distributed systems background and experience with Python or Rust.

Qualifications

  • Significant software engineering experience, particularly with distributed systems.
  • Results-oriented with bias toward impact and flexibility.
  • Willingness to take on extra duties outside the job description.
  • Interest in learning more about machine learning systems and infrastructure.

Responsibilities

  • Design, build, and maintain distributed systems that serve Claude to millions of users.
  • Develop resilient, flexible systems that adapt in real time to events.
  • Develop intelligent request routing, load balancing, and traffic management across accelerators and clouds.
  • Maximize compute efficiency and optimize fleet cost via autoscaling and orchestration.
  • Build and operate production-grade deployment pipelines for new models.
  • Provide high-performance inference infrastructure for researchers.

Skills

Distributed systems
High-performance systems
Python
Rust
Team collaboration

Education

Bachelor's degree or equivalent

Tools

Kubernetes
AWS
GCP
Azure
Python
Rust

Job description

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

Our Inference team is responsible for building and scaling the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry’s largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators.

The team has a dual mandate: maximizing compute efficiency to reliably serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms.

Inference systems are highly performance sensitive distributed systems. Inference serves hundreds of thousands of customers every day, and the size & span of the inference fleet requires sophisticated routing, scaling, and networking systems.

Key responsibilities
  • Design, build, and maintain the distributed systems that serve Claude to millions of users worldwide
  • Develop resilient, flexible systems that adapt in real time to real world events
  • Develop intelligent request routing, load balancing, and traffic management systems across thousands of accelerators and multiple cloud providers
  • Maximize compute efficiency and optimize cost across the fleet by autoscaling and orchestrating production, research, and experimental workloads across multiple cloud providers
  • Build and operate production-grade deployment pipelines for releasing new models to users
  • Provide high-performance inference infrastructure that enables researchers to develop next-generation models
  • Integrate new AI accelerator platforms and support inference for new model architectures
Minimum Qualifications
  • Significant software engineering experience, particularly with distributed systems
  • Results-oriented, with a bias towards flexibility and impact
  • Willingness to pick up slack, even if it goes outside your job description
  • Desire to learn more about machine learning systems and infrastructure
  • Thrive in environments where technical excellence directly drives both business results and research breakthroughs
  • Care about the societal impacts of your work
Preferred Qualifications
  • Experience with high-performance, large-scale distributed systems
  • Experience implementing and deploying machine learning systems at scale
  • Experience with load balancing, request routing, or traffic management systems
  • Familiarity with LLM inference optimization, batching, and caching strategies
  • Experience with Kubernetes and cloud infrastructure (AWS, GCP, Azure)
  • Proficiency in Python or Rust
Representative projects
  • Designing intelligent routing algorithms that optimize request distribution across many accelerators in different environments
  • Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads
  • Building production-grade deployment pipelines for releasing new models to millions of users reliably
  • Contributing to new inference features
  • Supporting inference for new model architectures
  • Analyzing observability data to tune performance based on real-world production workloads
  • Managing multi-region deployments and geographic routing for global customers
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.
Guidance on Candidates' AI Usage:

Learn about our policy for using AI in our application process.

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.

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