{"schemaVersion":"jobsearcher.job.v1","id":"48cb21401bb53e1859f74751","url":"https://jobsearcher.com/jobs/48cb21401bb53e1859f74751","canonicalUrl":"https://jobsearcher.com/jobs/48cb21401bb53e1859f74751","title":"ML Engineer- Multi Agent AI","description":"Job Overview\r\nYou will design and build autonomous multi-agent intelligence systems capable of perception, reasoning, coordination, and decision-making.\r\nYou will develop distributed AI agents that interact with real-world data, collaborate with other agents, and execute structured actions.\r\nYou will contribute to the architecture of DECTIFY's autonomous intelligence layer, enabling scalable, city-level coordination and predictive decision systems.\r\nRequired Skills\r\nStrong proficiency in Python.\r\nExperience designing or implementing multi-agent systems or distributed AI architectures.\r\nSolid understanding of Reinforcement Learning, Markov Decision Processes, and policy optimization methods.\r\nFamiliarity with graph-based reasoning, planning algorithms, or decision trees.\r\nAbility to build evaluation metrics beyond basic accuracy (reward optimization, convergence stability, coordination metrics).\r\nKey Responsibilities\r\nDesign and implement multi-agent AI architectures for real-time and asynchronous environments.\r\nDevelop autonomous decision-making pipelines integrating perception, reasoning, and action modules.\r\nBuild reinforcement learning or planning-based systems for task allocation, route optimization, and coordination.\r\nImplement inter-agent communication protocols and distributed intelligence frameworks.\r\nOptimize models for deployment across cloud and edge environments.\r\nBachelor's or equivalent experience in Computer Science, Computer Engineering, or a related technical field.\r\nDegree is preferred but skills, ownership, and mindset matter more.\r\nPreferred Skills\r\nExperience with Multi-Agent Reinforcement Learning (MARL).\r\nFamiliarity with simulation environments or agent training frameworks.\r\nResearch experience in autonomous systems or agent-based modeling.\r\nJ-18808-Ljbffr","company":"Dectify Technologies","rawCompany":"dectify technologies","city":"Mission","state":"KS","isRemote":false,"isActive":false,"createdAt":"2026-06-25T01:21:34.061Z","occupations":[{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"541690","title":"Other Scientific and Technical Consulting Services","slug":"other-scientific-and-technical-consulting-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"ML Engineer- Multi Agent AI","description":"Job Overview\r\nYou will design and build autonomous multi-agent intelligence systems capable of perception, reasoning, coordination, and decision-making.\r\nYou will develop distributed AI agents that interact with real-world data, collaborate with other agents, and execute structured actions.\r\nYou will contribute to the architecture of DECTIFY's autonomous intelligence layer, enabling scalable, city-level coordination and predictive decision systems.\r\nRequired Skills\r\nStrong proficiency in Python.\r\nExperience designing or implementing multi-agent systems or distributed AI architectures.\r\nSolid understanding of Reinforcement Learning, Markov Decision Processes, and policy optimization methods.\r\nFamiliarity with graph-based reasoning, planning algorithms, or decision trees.\r\nAbility to build evaluation metrics beyond basic accuracy (reward optimization, convergence stability, coordination metrics).\r\nKey Responsibilities\r\nDesign and implement multi-agent AI architectures for real-time and asynchronous environments.\r\nDevelop autonomous decision-making pipelines integrating perception, reasoning, and action modules.\r\nBuild reinforcement learning or planning-based systems for task allocation, route optimization, and coordination.\r\nImplement inter-agent communication protocols and distributed intelligence frameworks.\r\nOptimize models for deployment across cloud and edge environments.\r\nBachelor's or equivalent experience in Computer Science, Computer Engineering, or a related technical field.\r\nDegree is preferred but skills, ownership, and mindset matter more.\r\nPreferred Skills\r\nExperience with Multi-Agent Reinforcement Learning (MARL).\r\nFamiliarity with simulation environments or agent training frameworks.\r\nResearch experience in autonomous systems or agent-based modeling.\r\nJ-18808-Ljbffr","datePosted":"2026-06-25T01:21:34.061Z","dateModified":"2026-06-25T01:21:34.061Z","hiringOrganization":{"@type":"Organization","name":"Dectify Technologies","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mission","addressRegion":"KS","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"48cb21401bb53e1859f74751"},"url":"https://jobsearcher.com/jobs/48cb21401bb53e1859f74751"}}