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About the Role
Drive fast-paced research in frontier AI models, benchmarking, and evaluation, combining strong research credentials with exceptional engineering capabilities to move quickly from research questions to actionable results.
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.
Requirements
- 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 DeepMind is a strong advantage.
- Strong analytical and communication skills, with the ability to operate effectively in a fast-paced, customer-driven research environment.
- 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.
Skills
- AI
- Machine Learning
- LLMs
- Foundation Models
- Reasoning
- Agents
- Model Evaluation
- Benchmarking
- Python
- PyTorch
- AI for Cybersecurity
- Autonomous Security Agents
- Vulnerability Research
- Penetration-Testing Automation
- Security Operations
- Security of AI
- LLM Red Teaming
- Adversarial Machine Learning
- Prompt Injection
- Agentic AI Security
- Cybersecurity Tools
- CTFs
- Sandboxed Exploitation Environments
- Static/Dynamic Code Analysis
- Security Testing Frameworks
Experience Level
- Principal
Education Level
- PhD or MSc in Computer Science, AI, Machine Learning, or a related field
About the Company
- 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.
- If you're creative and driven to secure the future of AI, we want to hear from you!