# Software Engineer, Research Infrastructure

**Company:** [Anthropic](https://hotfix.jobs/companies/anthropic)
**Location:** San Francisco, CA, New York, NY
**Role:** ML Engineering
**Salary:** $405k – $625k/yr
**Experience:** 7+ years
**Skills:** Distributed Systems, Large-Scale Infrastructure, Cloud Infrastructure, Infrastructure As Code, Machine Learning Workflows, Research Infrastructure
**Posted:** 2026-07-06

> Build and scale research infrastructure and distributed systems at Anthropic to accelerate ML research workflows. Independently lead complex multi-month projects, drive cross-org alignment, and partner with researchers in a fast-evolving, ambiguous environment.

## Job Description

## Responsibilities
- Design, build, and scale infrastructure and systems that support rapidly increasing usage, where requirements and workload continue to evolve as the products built on top of them evolve
- Independently scope and lead complex, multi-month engineering projects, from an ambiguous starting point through to a production system
- Drive cross-organizational alignment on technical direction, working through ambiguous problem spaces with multiple stakeholders and teams
- Make architectural decisions that shape the foundation of research infrastructure and tooling across Anthropic
- Partner directly with researchers to deeply understand their workflows, then anticipate and design for how those needs will change
- Iterate quickly, favoring pragmatic, first-principles solutions and fast feedback loops over heavy upfront design
- Take ownership of the reliability and scalability of critical systems as load, usage, and complexity increase
- Help set technical standards and best practices for the team, and mentor other engineers

## Minimum Qualifications
- Experience designing, building, and operating large-scale distributed systems or infrastructure in production
- A track record of independently scoping and delivering complex, ambiguous, multi-month technical projects
- Strong software engineering fundamentals and hands-on coding ability
- Experience making architectural decisions that other engineers and teams build on top of
- Strong written and verbal communication skills, with experience driving alignment across multiple teams or stakeholders
- Demonstrated ability to operate effectively in ambiguous, fast-changing environments

## Preferred Qualifications
- Experience building infrastructure or platforms specifically for research or machine learning workflows
- Direct experience navigating the reliability and architectural challenges that come with rapidly scaling systems
- Experience with distributed systems, cloud infrastructure, and infrastructure-as-code
- Familiarity with the compute, tooling, and workflow needs of large-scale machine learning research
- Experience operating in a startup or startup-like environment, i.e. a small, fast-moving team with high autonomy
- Prior experience as a technical lead or mentor for other engineers

## Compensation
Annual Salary: $405,000—$625,000 USD

Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

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