Lila Sciences
Technology
Co-Op,AISecurity
Neural analysis suggests this role is
optimal for Entry candidates.
“Co-Op, AI Security at Lila Sciences. Skills: AI Security, LLM Security, Agent Governance, Prompt Engineering. Identify AI/ML security vulnerabilities. Analyze AI/ML security vulnerabilities”
Industry & Context.
Root cause analysis
What They're Looking For.
Must Have
Computer Science program enrollment, Cybersecurity program enrollment, Information Security program enrollment, Foundational cybersecurity concepts, Basic LLM familiarity, Basic AI agent familiarity, Scripting in Python, Clear written communication, Attention to detail, Willingness to dig into systems
Nice to Have
AI/ML security coursework, Adversarial ML coursework, LLM red-teaming coursework, Cloud platforms exposure, Security tooling familiarity, Hands-on AI agent experience, Hands-on prompt pipeline experience, Hands-on RAG systems experience
What You'll Do.
Identify AI/ML security vulnerabilities
Analyze AI/ML security vulnerabilities
Participate in threat modeling
Recommend security mitigations
Review AI/ML application code
Test AI/ML application code
Review AI/ML configurations
Test AI/ML configurations
Research AI security threats
Compile findings into documentation
Develop security tests
Develop proof-of-concepts
Run proof-of-concepts
How You'll Work.
Team & Collaboration
Cross-functional teams; ML engineers; Product managers; Security architects
Communication Scope
Technical documentation
Full Job Description
Your Impact at LILA Lila Sciences is building the world's first scientific super intelligence platform. As AI agents and automated systems handle more of the research and operations workload, securing them has become a core focus for the IT & Security team. This Co-Op role focuses on the AI side of that work. You will join the IT & Security team and contribute to projects that evaluate, harden, and monitor the AI tools, agents, and automation pipelines Lila depends on. Expect exposure to areas most academic programs don't cover yet: agent governance, prompt-level threats, model deployment risks, and AI-driven security automation. The role is structured for someone curious, technical, and looking to build applied experience. You will own specific projects, work alongside security engineers, and finish the term with hands-on work in a domain that is still being defined. What You'll Be Building Assist in identifying and analyzing AI/ML security vulnerabilities, including prompt injection attacks, model poisoning, and data poisoning risks Participate in threat modeling exercises for AI systems and recommend security mitigations Review and test AI/ML application code and configurations for security issues Research emerging AI security threats and compile findings into technical documentation Develop and run security tests and proof-of-concepts for AI model robustness Collaborate with cross-functional teams including ML engineers, product managers, and security architects What You'll Need to Succeed Currently enrolled in a Computer Science, Cybersecurity, Information Security, or related program. Foundational understanding of cybersecurity concepts: authentication, encryption, network basics. Basic familiarity with how large language models and AI agents work. Comfortable scripting in Python or a similar language. Clear written communication for documenting security findings. Strong attention to detail and willingness to dig into unfamiliar systems. Bonus Points For Cours
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