Principal AI Research Cybersecurity Scientist; Bay Area)

We are seeking a highly technical, hands-on Principal AI Research Cybersecurity Scientist to drive fast-paced research in frontier AI models, benchmarking, and evaluation.

The ideal candidate combines strong research credentials with exceptional engineering capabilities and a proven ability to execute rapid research cycles, moving quickly from identifying research questions to building prototypes, running experiments, and delivering actionable results.

The role requires deep expertise in LLMs, foundation models, reasoning, agents, and model evaluation, alongside the ability to translate complex customer challenges into measurable research outcomes.

Key Responsibilities

• Conduct hands-on research in frontier AI models, reasoning, agents, and multimodal systems.
• Design, implement, and iterate on AI benchmarks, evaluation frameworks, and experimental pipelines.
• Execute short, high-impact research cycles, rapidly moving from hypotheses to experiments, prototypes, and validated findings.
• Identify model limitations, evaluation gaps, and emerging research opportunities.
  
  Work directly with customers and technical stakeholders to translate complex challenges into actionable research.
• Collaborate with engineering and product teams to turn research findings into practical solutions.

Qualifications

• PhD or MSc in Computer Science, AI, Machine Learning, or a related field, with strong relevant research experience.
• Strong publication record at leading AI/ML conferences such as NeurIPS, ICML, ICLR, ACL, or equivalent venues.
• Exceptional hands-on technical capabilities, including advanced Python, PyTorch, and experience building and evaluating complex AI systems.
• Proven ability to independently design, implement, and execute research experiments within short development cycles.
• Deep understanding of LLMs, foundation models, benchmarking, and evaluation methodologies.
• Experience with frontier AI labs such as OpenAI, Anthropic, or Google Deep Mind is a strong advantage.
• Strong analytical and communication skills, with the ability to operate effectively in a fast-paced, customer-driven research environment.

Preferred Qualifications

• Experience with AI for Cybersecurity, including autonomous security agents, vulnerability research, penetration-testing automation, or security operations.
• Experience with Security of AI, including LLM red teaming, adversarial machine learning, prompt injection, and agentic AI security.
• Familiarity with cybersecurity tools and environments such as CTFs, sandboxed exploitation environments, static/dynamic code analysis, and security testing frameworks.
• Experience developing cybersecurity benchmarks or evaluating frontier models on complex security-related tasks.

Alice is a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact- whether with each other or with machines.

In a world where AI has fundamentally changed the nature of risk, Alice provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection.

Alice is widely considered a global leader in online safety and AI security. We have some of the most forward-thinking and passionate minds in the world working to safeguard over 3 billion users across the largest AI and tech platforms.

We are seeking a highly technical, hands-on Principal AI Research Cybersecurity Scientist to drive fast-paced research in frontier AI models, benchmarking, and evaluation.

The ideal candidate combines strong research credentials with exceptional engineering capabilities and a proven ability to execute rapid research cycles, moving quickly from identifying research questions to building prototypes, running experiments, and delivering actionable results.

The role requires deep expertise in LLMs, foundation models, reasoning, agents, and model evaluation, alongside the ability to translate complex customer challenges into measurable research outcomes.

Key Responsibilities

• Conduct hands-on research in frontier AI models, reasoning, agents, and multimodal systems.
• Design, implement, and iterate on AI benchmarks, evaluation frameworks, and experimental pipelines.
• Execute short, high-impact research cycles, rapidly moving from…