Model Performance Software Engineer, Claude Code

Anthropic; San Francisco (CA); On-site; USD 320,000 - 485,000; Full time

Benefits offered by this job

Competitive compensation

Generous vacation and parental leave

Flexible working hours

Job summary

A leading AI research firm based in San Francisco is seeking a Software Engineer to collaborate with researchers on improving coding capabilities in AI systems. This role involves designing evaluation systems, developing tooling for researchers, and taking ownership of complex engineering challenges. Candidates should have at least 5 years of experience and be excited to work at the intersection of engineering and AI research. A Bachelor's degree in a relevant field is required, and competitive compensation is offered.

Qualifications

• At least 5 years of work experience.
• Strong product intuition to inform necessary capabilities.
• Experience in high-performance environments is a plus.

Responsibilities

• Design and build evaluation systems for model capabilities.
• Build tooling that enables researchers to run experiments.
• Develop pipelines for data collection and analysis.

Skills

Complex systems

Fast-paced environments

Agentic coding tools

Problem ownership

Reliability

Education

Bachelor's degree in a related field

Tools

Python

TypeScript

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

We’re looking for a Software Engineer to work at the intersection of engineering and research on the Claude Code team. In this role, you’ll collaborate directly with Anthropic’s researchers to improve Claude’s coding capabilities through tooling, infrastructure, and evaluations. You’ll build systems that help us understand where Claude Code excels and where it falls short—and then help close those gaps.

We’re looking for engineers who can build robust, complex systems and who thrive in fast‑paced, high‑intensity environments. You’ll take ambiguous problems and turn them into reliable infrastructure that accelerates our research.

Responsibilities

• Design and build evaluation systems that measure model capabilities across diverse coding tasks
• Build tooling and infrastructure that enables researchers to run experiments at scale
• Develop pipelines for data collection, processing, and analysis
• Create internal tools that improve researcher productivity and accelerate iteration cycles
• Serve as a bridge between product and research—bring strong product intuition to inform which capabilities matter most
• Work closely with researchers to translate research questions into engineering solutions
• Own systems end‑to‑end—from design through production reliability

You May Be a Good Fit If You

• Have built and owned complex systems—pipelines, infrastructure, or software that orchestrates many components and handles significant state and logic
• Thrive in high‑intensity environments with fast iteration cycles
• Take full ownership of problems and drive them to completion independently
• Are a power user of agentic coding tools and have strong intuition about model capabilities and limitations
• Are comfortable diving into unfamiliar technical domains and figuring things out quickly
• Care deeply about correctness and reliability in the systems you build
• Are excited to work at the boundary between engineering and AI research
• Have at least 5 years of work experience

Strong Candidates May Also Have Experience With

• Writing or maintaining eval/evaluation frameworks
• Reinforcement learning systems
• Working in high‑performance, demanding environments—trading firms, quant funds, competitive research labs, or fast‑moving startups where intensity is the norm
• Have research computing or scientific infrastructure background
• Have a strong quantitative foundation (math, physics, or related fields)
• Python and TypeScript

Annual Salary

$320,000—$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. 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.

Additional Information

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.