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Jobs/New York City/Staff Research Engineer, Discovery Team
New York City, NY

Staff Research Engineer, Discovery Team

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.

Company
Anthropic
Compensation
Not listed
Schedule
Full-Time
Role overview

What this role actually needs.

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. Responsibilities: - Working across the full stack to identify and remove bottlenecks preventing progress toward scientific AGI - Develop approaches to address long-horizon task completion and complex reasoning challenges essential for scientific discovery - Scaling research ideas from prototype to production - Create benchmarks and evaluation frameworks to measure model capabilities in scientific workflows and computer use - Implement distributed training systems and performance optimizations to support large-scale model development Company context: Anthropic is an AI safety company building Claude, a frontier-model assistant for developers, enterprises, and consumers.

Responsibilities

Day-to-day expectations

Anthropic lists these responsibilities for the Staff Research Engineer, Discovery Team role.

  • Working across the full stack to identify and remove bottlenecks preventing progress toward scientific AGI
  • Develop approaches to address long-horizon task completion and complex reasoning challenges essential for scientific discovery
  • Scaling research ideas from prototype to production
  • Create benchmarks and evaluation frameworks to measure model capabilities in scientific workflows and computer use
  • Implement distributed training systems and performance optimizations to support large-scale model development
UpJobz market context

Why this listing is more than a copied job post.

Staff Research Engineer, Discovery Team is framed against UpJobz source checks, country scope, compensation visibility, and work-authorization signals so candidates can make a faster go/no-go decision.

United States tech market

United States roles on UpJobz are filtered for high-tech relevance, source freshness, and actionable employer detail before they are allowed into SEO surfaces.

Compensation read

The employer source does not expose a reliable salary range, so candidates should ask for compensation early instead of waiting until late-stage interviews.

Work authorization read

Current extracted signal: Open to TN, H-1B, and OPT candidates already in the United States. UpJobz treats this as a search signal, not legal advice, and links visa-sensitive roles back to the relevant visa hub where possible.

Location read

On-site roles in New York City should be compared against commute, local salary bands, and nearby employer demand.

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Next moves

  • Tailor your resume around ai and llm instead of sending a generic application.
  • Use the first two bullets of your application to connect your background directly to staff research engineer, discovery team is a high-signal on-site role in new york city, and it is most realistic for open to tn, h-1b, and opt candidates already in the united states.
  • Open the role quickly if it fits and bookmark three similar jobs before you leave the page.

Interview themes

Artificial IntelligenceOn-siteaillmmachine-learningresearch

Watchouts

  • Compensation is hidden, so get range clarity in the first recruiter conversation.
  • Use open to tn, h-1b, and opt candidates already in the united states as part of your positioning so the recruiter does not have to infer it.
  • Show concrete examples of succeeding in on-site environments.
Role signals

Keywords to match against your background

Use these terms to decide whether your resume, portfolio, and recent projects line up with the role.

aillmmachine-learningresearchkubernetesawsapisafetypython
Next step

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Source: job-boards.greenhouse.io · Source ID: 4593216008 · Confidence: 97/100 · Last checked: May 7, 2026

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