ML Engineer- Multi Agent AI

Job Overview You will design and build autonomous multi-agent intelligence systems capable of perception, reasoning, coordination, and decision-making. You will develop distributed AI agents that interact with real-world data, collaborate with other agents, and execute structured actions. You will contribute to the architecture of DECTIFY's autonomous intelligence layer, enabling scalable, city-level coordination and predictive decision systems. Required Skills Strong proficiency in Python. Experience designing or implementing multi-agent systems or distributed AI architectures. Solid understanding of Reinforcement Learning, Markov Decision Processes, and policy optimization methods. Familiarity with graph-based reasoning, planning algorithms, or decision trees. Ability to build evaluation metrics beyond basic accuracy (reward optimization, convergence stability, coordination metrics). Key Responsibilities Design and implement multi-agent AI architectures for real-time and asynchronous environments. Develop autonomous decision-making pipelines integrating perception, reasoning, and action modules. Build reinforcement learning or planning-based systems for task allocation, route optimization, and coordination. Implement inter-agent communication protocols and distributed intelligence frameworks. Optimize models for deployment across cloud and edge environments. Bachelor's or equivalent experience in Computer Science, Computer Engineering, or a related technical field. Degree is preferred but skills, ownership, and mindset matter more. Preferred Skills Experience with Multi-Agent Reinforcement Learning (MARL). Familiarity with simulation environments or agent training frameworks. Research experience in autonomous systems or agent-based modeling. J-18808-Ljbffr