Research Intern - AI Security

Exponential; Tübingen; Hybrid; EUR 13,000 - 20,000; Part time

Benefits offered by this job

Flexible hours

Remote-friendly setup

Conference budget

Research freedom

Job summary

Exponential in Tübingen offers a hybrid internship to build security environments and evaluate agent training methods for frontier AI systems. You will own a technically ambitious project, from design to experiments and communicating results, alongside a core team.

We welcome students or recent researchers in ML, CS, or security with strong programming skills and curiosity about AI agents. Flexible hours and remote-friendly setup are provided, with opportunities for conference budgets and

Qualifications

• Current study or recent work in machine learning, computer science, security, or a related field.
• Strong programming skills and experience building or evaluating machine-learning systems.
• Curiosity about AI agents and the discipline to investigate failures carefully.
• Ability to work independently and ask for feedback early.

Responsibilities

• Develop and evaluate security environments, agent training methods, attacks, or defenses.
• Run controlled experiments with clear baselines and verifiable outcomes.
• Analyze model behavior and communicate the results to the team.
• Contribute code, evaluations, and research findings that remain useful after the internship.

Skills

Programming

ML Systems

Independent Work

Education

Student in CS/ML

Tools

Python

PyTorch

Job description

Build security environments, adversarial agents, and evaluations for frontier AI systems.

Location: Tübingen / Hybrid
Employment: Internship

The role

You will work across AI security, machine learning, and research engineering alongside the core team. You will take ownership of a technically ambitious project in agent security, from designing and implementing the approach to running experiments and communicating the results.

What you’ll work on

• Develop and evaluate security environments, agent training methods, attacks, or defenses

• Run controlled experiments with clear baselines and verifiable outcomes

• Analyze model behavior and communicate the results to the team

• Contribute code, evaluations, and research findings that remain useful after the internship

What we’re looking for

• Current study or recent work in machine learning, computer science, security, or a related field

• Strong programming skills and experience building or evaluating machine-learning systems

• Curiosity about AI agents and the discipline to investigate failures carefully

• Ability to work independently and ask for feedback early

Useful experience

• LLMs, reinforcement learning, or agentic systems

• Adversarial machine learning, red teaming, or AI safety evaluations

• Research codebases, reproducible experiments, or open-source contributions

• A previous research project, thesis, or technical publication

What we offer

• Competitive compensation

• Flexible hours and a remote-friendly setup

• Vacation, learning, and conference budget

• Research freedom in a high-trust environment