Research Engineer (Physical Ai)
Pubblicato il 26-09-2026 - Generali Group in Trieste
Overview
In this role you advance the intelligence layer for autonomous industrial systems, collaborating with AI and engineering leaders.
You'll prototype multi-agent and collective approaches and integrate them with robotic platforms and industrial infra.
You design robust experiments to evaluate system-level behavior and work across research and hardware teams to deliver real-world impact.
The role blends research excellence with production-ready implementations in a hybrid Trieste environment.
Retribuzione / Benefits
Lavoro da remoto and flexible hours
Corporate welfare system
Meal vouchers
Supplementary health insurance
Wellbeing initiatives
Training and development
Responsabilità
Research and prototype multi-agent and collective intelligence approaches from simulation to real-system integration
Build the intelligence and coordination layer interfacing with physical systems and robotics infrastructure
Design rigorous system-level experiments to validate emergent behavior
Integrate AI systems with external engineering stacks via clean interfaces and contracts
Define evaluation frameworks for collective/adaptive behavior and performance degradation
Stay current with multi-agent, swarm intelligence, and autonomous systems research and translate to applicable solutions
Requisiti fondamentali
Master's degree or PhD in a STEM field
At least 3–5 years of experience in multi-agent systems, autonomous systems, or collective intelligence with real implementations
At least 3–5 years of experience in simulation tools/methodologies ahead of hardware integration
Experience integrating AI with physical infrastructure or robotic platforms; comfortable with robotic middleware at an operational level
Entrepreneurial mindset with autonomous, proactive attitude
Strong collaboration with external engineering teams
Excellent communication and stakeholder management (tech/UI and executive level)
LLM-based systems; classical ML; APIs; microservices; inference optimization
Strong software engineering fundamentals; ability to transition experimental code to production
Experience at the research/engineering boundary: controlled experiments and production services