Member of Technical Staff - AI Security

Exponential Security Labs; Tübingen; Hybrid; EUR 90.000 - 125.000; Vollzeit

Benefits dieser Stelle

Equity

Remote-friendly setup

Conference budget

Professional development

Zusammenfassung

Exponential Security Labs in Tübingen offers a hybrid, full-time research role focused on AI security, ML, and systems engineering. You design reinforcement-learning environments, train adversarial agents, and build evaluations for capable AI systems.

You will turn research results into benchmarks, training methods, and tooling, collaborating across security and ML disciplines in a flexible, remote-friendly environment with competitive compensation and growth opportunities.

Qualifikationen

• Proven track record in ML, security, or systems.
• Strong software and ML engineering fundamentals.
• Experience with LLMs, agentic systems, or reinforcement learning.

Aufgaben

• Design security environments for training and evaluating AI agents.
• Post-train agents using reinforcement learning and develop adaptive red-teaming methods.
• Evaluate frontier models and agentic systems.
• Turn research results into benchmarks, training methods, and tools.

Kenntnisse

Machine learning

Security

Systems

Jobbeschreibung

Build security environments, train adversarial agents, and evaluate frontier AI systems.

Location: Tübingen / Hybrid
Employment: Full-time

The role

You will work across AI security, machine learning, and research engineering. You will design reinforcement-learning environments, train adversarial agents, and build evaluations for capable AI systems.

What you’ll work on

• Design security environments for training and evaluating AI agents
• Post-train agents using reinforcement learning and develop adaptive red-teaming methods
• Evaluate frontier models and agentic systems
• Turn research results into benchmarks, training methods, and tools

What we’re looking for

• A strong track record in machine learning, security, or systems
• Strong software and machine-learning engineering fundamentals
• Experience with LLMs, agentic systems, or reinforcement learning
• Ability to run careful experiments and communicate results clearly

Useful experience

• AI security, red teaming, or adversarial machine learning
• Reinforcement learning or post-training for language models
• Research engineering or production ML systems
• Published research or substantial open technical work

What we offer

• Competitive compensation with equity
• Flexible hours and a remote-friendly setup
• Vacation, learning, and conference budget
• Research freedom in a high-trust environment