Research Engineer in AI-driven Social Simulations
Core
Building large-scale AI simulations of societal processes (environmental negotiations, nature conservation, hybrid-threat scenarios) using autonomous LLM agents to map policy outcomes and stress-test decisions.
Role type
Research Engineer (AI-driven Social Simulations)
Builds
Multi-agent simulation framework with LLM-powered autonomous agents, GPU-enabled HPC clusters, and validation methodologies.
Domain
Ecology, political science, computational social science, and complex system analysis.
Deliverable
production ML models | research
Required skills
Python, machine learning/deep learning, software engineering (version control, testing, modular design), GPU workflows, Monte Carlo simulations
Preferred skills
LLMs (APIs/local deployment), deep reinforcement learning, agent-based modelling, high-performance computing, complex adaptive systems
Technologies
Python, LLMs, GPU, HPC clusters (NAISS)
Responsibilities
Build LLM-agent infrastructure with multi-tier memory and affect states; extend and maintain multi-agent simulation framework; run large-scale Monte Carlo simulations on HPC; co-author scientific publications.
Seniority
Mid-level Research Engineer
