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Posted 3 months ago

Staff + Senior Software Engineer, Inference

@ Anthropic

Ontario

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Overview

Anthropic is hiring a Staff and Senior Software Engineer for its Inference team, which builds and runs the systems that serve Claude to millions of users worldwide. The role covers distributed systems, request routing, fleet orchestration across AI accelerators, and model deployment pipelines. The posting states a hybrid policy of at least 25% time in an office and visa sponsorship available for some roles.

Responsibilities:

  • Design and maintain distributed systems serving Claude to millions of users
  • Build intelligent request routing and load balancing across thousands of accelerators
  • Autoscale and orchestrate production, research and experimental compute workloads
  • Build production-grade pipelines for releasing new models

Requirements summary:

  • Significant software engineering experience, especially distributed systems
  • Bias toward flexibility and impact
  • Desire to learn machine learning systems and infrastructure
  • Care about societal impacts of the work

Tools & skills

Benefits mentioned

Paid time offParental leave
Source and dates

Employer career site / ATS feed · greenhouse

Employer posting date
2026-08-17
First seen by our source
2026-10-08
Source record updated
2026-11-06

These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.

Job details

SenioritySenior
DepartmentSoftware development
Work settingOffice
PositionMostly sitting
Physical demandsphysical low · computer high
EducationBachelor’s degree (required)
Fields of studyA field relevant to the role as demonstrated through coursework, training, or pr
Perks mentionedGenerous paid time off, Flexible hours, Generous parental leave, Stock or equity

Summary and details written by AI from the posting; the employer’s posting is the authority.

Anthropic

Saved company profile

Historical company information from a saved The Jobs API profile (LinkedIn/Crunchbase fields). It is not live-verified; figures may have changed. Missing values remain unknown.

Anthropic is an AI safety and research company working to build reliable, interpretable, and steerable AI systems.

Full company description

We're an AI research company that builds reliable, interpretable, and steerable AI systems. Our first product is Claude, an AI assistant for tasks at any scale. Our research interests span multiple areas including natural language, human feedback, scaling laws, reinforcement learning, code generation, and interpretability.

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  • Anthropic
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Reported total investment
63,740,377,627

Currency and observation date were not supplied; this is not a current valuation or a funding round.

We're an AI research company that builds reliable, interpretable, and steerable AI systems. Our first product is Claude, an AI assistant for tasks at any scale. Our research interests span multiple areas including natural language, human feedback, scaling laws, reinforcement learning, code generation, and interpretability.

FieldValue
IndustryResearch Services
Company size501-1,000 employees
HeadquartersSan Francisco
Organization typePrivately Held
Open jobs on Jobsy8
LinkedInView page
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 maintaining 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

  • Maximize compute efficiency across the fleet by autoscaling and orchestrating production, research, and experimental workloads

  • 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

Deadline to apply: None. Applications will be reviewed on a rolling basis.

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.

For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.

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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