Simulation Research Scientist

3+ years of experience in software simulation, system modeling, or performance testing for distributed systems Strong expertise in simulation frameworks like Gazebo, PyBullet, CARLA, or similar for creating virtual environments Proficiency in Python, Go, or C++ for real-time simulation development and system integration Experience with distributed systems, microservices architecture, and CI/CD pipelines in large-scale environments Knowledge of multi-agent reinforcement learning (MARL) principles and AI-driven optimization techniques for software systems Experience with performance monitoring, load balancing, and task scheduling in complex development infrastructures Familiarity with build systems (e.g., Jenkins, CircleCI, etc.), containerization (e.g., Docker), and cloud infrastructure (AWS, GCP, Azure)

Develop and maintain high-fidelity simulation environments for software build systems and remote execution processes Implement performance models for build caching, task distribution, and system coordination in large-scale development environments Create virtual testbeds for optimizing software compilation, testing workflows, and CI/CD pipeline automation Integrate multi-agent simulation for real-time task coordination and resource allocation across distributed build systems Work with Hardware-in-the-Loop (HIL) and Software-in-the-Loop (SIL) frameworks to validate build performance Optimize simulation workflows to validate build efficiency, cache hit rates, and task execution accuracy Collaborate with engineering, AI, and product teams to ensure consistency between simulation and real-world software builds