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Research Engineer, Discovery

Anthropic - San Francisco, CA

Posted May 14, 2025

Benefits

Parental leave
Not verified
Non-birth-parent leave
Not verified
Family-building benefits
  • Fertility benefits: Not verified
  • Adoption assistance: Not verified
  • Surrogacy assistance: Not verified
Mental health support
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Relocation assistance
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Childcare support
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Learning budget
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Verification
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Salary
$350K-$850K From the posting source checked Jun 20, 2026
401(k) match
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Market context

U.S. role benchmark (BLS OEWS)
$116,543 U.S. median for this role
Projected growth (BLS Employment Projections)
+9.8% - Much faster than average

415% above the BLS role benchmark for software engineering aggregate.

Posted salary is far from this role benchmark; treat it as low confidence.

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function
Engineering From the posting source checked Jun 20, 2026
Seniority
Mid From the posting source checked Jun 20, 2026

Schedule

Shift type
Not verified
Weekend work
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Company

Company stage
Public-company From the posting source checked Jun 20, 2026
Equity
Offered From the posting source checked Jun 20, 2026

Application

Cover letter
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Assessment
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Deadline
Not stated

Where they hire

State eligibility is not yet verified.

About this role

Research Engineer, Discovery San Francisco, CA 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 Team Our team is organized around the north star goal of building an AI scientist - a system capable of solving the long term reasoning challenges and basic capabilities necessary to push the scientific frontier. About the role As a Research Engineer on our team you will work end to end across the whole model stack, identifying and addressing key infra blockers on the path to scientific AGI. Strong candidates should have familiarity with elements of language model training, evaluation, and inference and eagerness to quickly dive and get up to speed in areas they are not yet an expert on. This may include performance optimization, distributed systems, VM/sandboxing/container deployment, and large scale data pipelines. Join us in our mission to develop advanced AI systems pushing the frontiers of science and benefiting humanity. Responsibilities: - Design and implement large-scale infrastructure systems to support AI scientist training, evaluation, and deployment across distributed environments - Identify and resolve infrastructure bottlenecks impeding progress toward scientific capabilities - Develop robust and reliable evaluation frameworks for measuring progress towards scientific AGI. - Build scalable and performant VM/sandboxing/container architectures to safely execute long-horizon AI tasks

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