[Hiring] Data Science - Agentic AI Intern @Cobalt

Role Description

We are pushing the boundaries of agentic AI in the offensive security space, leveraging over 10 years of real-world offensive security data to train and evaluate our models. Our work sits at the intersection of applied mathematics, statistical modeling, and autonomous AI systems, focused on high-stakes, adversarial environments.

We are seeking a graduate-level Data Science Intern with a strong foundation in applied mathematics or statistics and hands-on experience with agentic AI systems. In this role, you will contribute to the development of autonomous agents, improving their ability to reason, adapt, and exploit findings in both test and real-world environments. You will also develop models that capture complex system interactions and evaluate how agents perform under evolving platform conditions.

What You’ll Work On

• Build and improve autonomous agents, focusing on reasoning, planning, and exploitation workflows
• Enhance agent performance in both simulated and real-world environments
• Analyze outputs from agents to identify system weaknesses and emergent behaviors
• Collaborate with engineering and security teams to integrate models and agents into real-world offensive security workflows
• Apply techniques from:
  • causal inference
  • probabilistic modeling
  • optimization

Responsibilities

• Design and run experiments to validate model and agent assumptions
• Work with large-scale datasets to calibrate and test models
• Iterate on agent behavior based on empirical results and failure analysis
• Communicate findings clearly to technical stakeholders

Qualifications

• Graduate student (MS/PhD) in a quantitative field
• Strong foundation in at least one of: applied math, probability, statistics, and modeling
• Proficiency in Python
• Experience with agentic LLM-based AI systems

Nice-to-Haves

• Familiarity with offensive security concepts
• Experience with causal inference, simulation, or RL/planning
• Research, publications, or open-source contributions

Why You Should Join Us

• Ownership of a high-impact, technically challenging project
• Exposure to real-world applications of agentic AI
• Mentorship from experienced researchers and engineers
• Opportunity to contribute to systems at the intersection of data science, AI, and security