Staff / Senior Software Engineer, Inference

Anthropic; San Francisco (CA); On-site; USD 300,000 - 485,000; Full time

Benefits offered by this job

Competitive salary

Flexible working hours

Generous vacation and parental leave

Job summary

A forward-thinking AI company in San Francisco is seeking an experienced software engineer to join their Inference team. The role focuses on building and optimizing systems for AI model deployment, with a strong emphasis on technical excellence and societal impact. Candidates should possess solid software engineering experience, particularly in distributed systems, and be eager to work in a collaborative environment. Competitive salary range of $300,000 to $485,000 USD and hybrid work policy are offered.

Qualifications

• Experience with large-scale distributed systems is a plus.
• Experience with machine learning systems at scale is a plus.
• Experience with load balancing and traffic management is a plus.
• Optimizing LLM inference and caching strategies is advantageous.

Responsibilities

• Building and maintaining inference systems for AI models.
• Designing routing algorithms for request distribution.
• Autoscaling compute fleet according to demand.
• Managing multi-region deployments and analysis of observability data.

Skills

Software engineering experience

Distributed systems

Flexibility

Impact-oriented

Pair programming

Understanding of machine learning systems

Technical excellence

Concern for societal impacts

Education

Bachelor's degree in a related field

Tools

Kubernetes

Cloud infrastructure (AWS, GCP)

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 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.

You may be a good fit if you:

• Have significant software engineering experience, particularly with distributed systems
• Are results-oriented, with a bias towards flexibility and impact
• Pick up slack, even if it goes outside your job description
• Enjoy pair programming (we love to pair!)
• Want 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

Strong candidates may also have experience with:

• High-performance, large-scale distributed systems
• Implementing and deploying machine learning systems at scale
• Load balancing, request routing, or traffic management systems
• LLM inference optimization, batching, and caching strategies
• Kubernetes and cloud infrastructure (AWS, GCP)
• 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.

Compensation

The expected base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.

Annual Salary: $300,000 — $485,000 USD

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. 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. Guidance on Candidates\' AI Usage: Learn about our policy for using AI in our application process