AI Red Teamer, CBRNE

🔥 9 hours ago

🇺🇸 United States – Remote

💵 $65 - $158 / hour

⏳ Contract/Temporary

🟡 Mid-level

🟠 Senior

🤖 Artificial Intelligence

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 0%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Handshake

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2014

💼 Consulting

🏥 Healthcare

📦 Logistics

Consulting • Healthcare • Logistics

Handshake is a platform that connects students with potential employers and career centers, offering tools to streamline the recruiting process for its users. It provides features such as job postings, talent engagement suites, and event management for both virtual and in-person recruiting events. Handshake is widely used by Fortune 100 companies and offers integrations with existing automated tracking systems. It aims to build early career networks and supports a diverse range of Gen Z talent with a focus on improving hiring outcomes through proprietary data and advanced recruiting strategies.

📋 Description

• Evaluate whether AI models appropriately handle queries related to chemical, biological, radiological, nuclear, and explosive threats • Design technically grounded adversarial prompts testing whether models provide meaningful uplift toward CBRNE threats • Evaluate model outputs for technical accuracy and dangerous information • Probe dual-use knowledge boundaries involving scientific, medical, industrial, and weapons applications • Test multi-step and multi-turn attack chains • Score model responses against structured harm taxonomies and severity rubrics • Document findings with clear technical reasoning • Distinguish open-literature information from genuine operational uplift • Contribute to CBRNE-specific evaluation frameworks and threat models • Collaborate with red teamers, AI researchers, and policy teams to translate findings into model improvements • Stay current on model capabilities, jailbreak techniques, and relevant domain developments

🎯 Requirements

• Graduate-level education or equivalent professional experience in a relevant CBRNE field (chemistry, biochemistry, microbiology, virology, nuclear physics, radiochemistry, materials science, munitions/ordnance, chemical engineering, or closely related disciplines) • Ability to evaluate the technical accuracy and real-world consequence of model outputs in your domain • Understanding of dual-use research concerns and the distinction between open-source knowledge and operationally significant uplift • Strong hands-on experience using multiple LLMs (ChatGPT, Claude, Gemini, open-source models, etc.) • Creative, adversarial problem-solving skills • Clear and precise written communication, including the ability to explain technical risk to non-specialist audiences • Strong ethical judgment and the ability to separate adversarial thinking from personal values • Self-directed, collaborative, and comfortable in feedback-heavy environments • Candidates must be able to engage with sensitive CBRNE-related material professionally and sustainably • Active or prior security clearance (Secret, Top Secret, or SCI) (nice to have) • Experience in threat assessment, WMD analysis, intelligence analysis, or arms control verification (nice to have) • Background in biosafety/biosecurity, chemical safety, nuclear nonproliferation, or explosive ordnance disposal (nice to have) • Familiarity with relevant regulatory frameworks including CWC, BWC, IAEA safeguards, ATF regulations, and Export Administration Regulations (nice to have) • Experience in red teaming, penetration testing, or structured adversarial evaluation (nice to have) • Familiarity with Python or scripting languages, LLM APIs, or evaluation tooling (nice to have) • Published research or professional presentations in a relevant CBRNE domain (nice to have) • Prior work in trust and safety, content moderation, or AI evaluation (nice to have)