Full-Time

Research Engineer

Frontier Red Team, Cbrn, Biosecurity

Confirmed live in the last 24 hours

Anthropic

Anthropic

1,001-5,000 employees

AI research for reliable and interpretable systems

Compensation Overview

$280k - $425kAnnually

Mid, Senior

H1B Sponsorship Available

San Francisco, CA, USA

Candidates must be based in the Bay Area for this role and are expected to be in the office at least 25% of the time.

Category
Bioinformatics
Computational Biology
Biology & Biotech
Required Skills
LLM
Python
Machine Learning
Requirements
  • strong software engineering, machine learning, or computational biology experience
  • some understanding of molecular biology, bioengineering, or bioinformatics
  • writing clean, well-documented code in Python
  • track record of using technical infrastructure to interface effectively with machine learning models
  • familiarity with prompting and engineering large language models
  • ability to balance research goals with practical engineering constraints
  • strong problem-solving skills
  • results-oriented mindset
  • excellent communication skills
  • ability to work in a collaborative environment
  • willingness to pick up slack, even if it goes outside job description
  • preference for fast-moving collaborative projects over extensive solo efforts
  • care about the societal impacts of AI
Responsibilities
  • Design, run, and analyze scientific experiments to advance our understanding of large language models
  • Lead technical design discussions to ensure our infrastructure can support both current needs and future research directions
  • Collaborate with other engineers to maintain our evaluations codebase
  • Work with external partners to develop novel evaluations to accurately assess the biosecurity implications of our models
  • Partner closely with researchers, data scientists, policy experts, and other cross-functional partners to advance Anthropic’s safety mission
Desired Qualifications
  • Wet lab experience in molecular biology
  • Developing evaluations or benchmarks for large language models
  • Previous experience in emerging technology policy, including in biosecurity or AI

Anthropic focuses on creating reliable and interpretable AI systems. Its main product, Claude, serves as an AI assistant that can manage tasks for clients across various industries. Claude utilizes advanced techniques in natural language processing, reinforcement learning, and code generation to perform its functions effectively. What sets Anthropic apart from its competitors is its emphasis on making AI systems that are not only powerful but also understandable and controllable by users. The company's goal is to enhance operational efficiency and improve decision-making for its clients through the deployment and licensing of its AI technologies.

Company Size

1,001-5,000

Company Stage

Series E

Total Funding

$15.9B

Headquarters

San Francisco, California

Founded

2021

Simplify Jobs

Simplify's Take

What believers are saying

  • Anthropic's Claude models dominate the text generation market in 2025.
  • AI model interpretability enhances trust and adoption, benefiting Anthropic.
  • AI safety focus positions Anthropic as a leader in mitigating security risks.

What critics are saying

  • Emerging competitors like DeepSeek threaten Anthropic's market share in text generation.
  • Unclear IP laws in Latin America pose legal risks for Anthropic.
  • Public critique by Thomas Wolf may affect Anthropic's investor confidence.

What makes Anthropic unique

  • Anthropic focuses on AI safety, transparency, and alignment with human values.
  • Claude AI assistant caters to diverse industries, enhancing operational efficiency.
  • Anthropic emphasizes collaborative AI development with its upgraded developer platform.

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Benefits

Flexible Work Hours

Paid Vacation

Parental Leave

Hybrid Work Options

Company Equity

Growth & Insights and Company News

Headcount

6 month growth

2%

1 year growth

8%

2 year growth

3%
PYMNTS
Mar 10th, 2025
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LatamList
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Artificial intelligence (AI) is transforming how startups develop their products and services, creating opportunities for efficiency, automation, and entirely new business models. As startups increasingly integrate AI into their workflows—whether through third-party platforms like OpenAI, Google, or Anthropic, or by fine-tuning open-source models like Meta’s Llama or DeepSeek—an increasingly urgent question arises: Who owns the intellectual property (IP) developed with AI—whether generated by an AI model, refined through AI tools, or built on top of an AI platform?While traditional software and content tend to involve established authorship and ownership structures, AI-generated outputs exist in a gray area. As courts, regulators, and policymakers grapple with the boundaries of AI-generated IP, startups that fail to establish clear ownership risk losing their competitive edge. While the U.S. and EU have begun issuing guidance on AI and IP, many Latin American (LatAm) jurisdictions still operate under outdated IP laws that do not account for AI-generated content, leaving companies exposed to a level of uncertainty that can be unsettling for founders and investors alike. Without a well-defined legal framework, competitors can replicate AI-driven products without repercussions, and investors may question the defensibility of a startup’s technology.While the U.S