Join Anthropic's Inference team to design and maintain distributed systems that serve AI models to millions of users worldwide.
Requirements
- Education
- Bachelor's degree
- Visa
- Sponsorship available
Benefits
Joblaze summary
In this role, the Staff and Senior Software Engineer on the Inference team at Anthropic will focus on designing and maintaining distributed systems that deliver AI capabilities to millions of users. Key skills include expertise in distributed systems, load balancing, and experience with cloud infrastructure, particularly Kubernetes. This position is ideal for seasoned engineers who thrive in collaborative environments and are passionate about the societal implications of AI. Anthropic emphasizes a cohesive team approach, working on large-scale research efforts to advance trustworthy AI.
Joblaze insights
- Listed today on Joblaze — tracked directly from Anthropic's career page.
- Anthropic has 413 other open roles including Product Manager, Platform, Policy Counsel, EMEA , Staff+ Security Engineer, Risk Engineering.
- 2425 active Python roles on Joblaze right now.
- 1213 active AWS roles on Joblaze right now.
- 1061 active Kubernetes roles on Joblaze right now.
- Salary band is above the typical range for AI/ML roles (median ~$190,900).
Quick facts
- Is the Staff + Senior Software Engineer, Inference role remote?
- It's hybrid — Anthropic expects some on-site time in San Francisco, USA.
- What's the salary range?
- Anthropic lists $320,000–$485,000 for this role.
- Where is the role based?
- Anthropic is hiring for this position in San Francisco, USA.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: AWS, Rust, Python, GCP, Kubernetes, Azure.
- Does Anthropic sponsor work visas for this role?
- Yes — the posting indicates visa sponsorship is available for the right candidate.
- What seniority level is this role?
- Anthropic targets staff-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Staff + Senior Software Engineer, Inference role at Anthropic.
From the original posting
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 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.
Key responsibilities
- Design, build, and maintain the distributed systems that serve Claude to millions of users worldwide
- 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
- Use observability data to tune and improve performance based on real-world production workloads
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
- Enjoy pair programming (we love to pair!)
- 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 thousands of accelerators
- 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
- Integrating new AI accelerator platforms to maintain our hardware-agnostic competitive advantage
- Contributing to new inference features (e.g., structured sampling, prompt caching)
- 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.
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.
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.