Neuro-Symbolic AI Manager - Synergyassure, Inc

Position Overview We are seeking few accomplished Neuro-Symbolic AI Manager to lead advanced research and productization efforts in hybrid AI systems that combine machine learning with symbolic reasoning. This role blends deep technical leadership with hands-on algorithm design, working at the forefront of explainable and high-performance AI solutions. Key Responsibilities 1. Technical Leadership & Strategy Define and drive the organization s neuro-symbolic AI roadmap in alignment with business objectives. Lead AI-driven initiatives from research concept through scalable production deployment. Mentor and guide multidisciplinary teams of AI researchers, engineers, and data scientists. 2. Algorithm Design & Implementation Architect, develop, and optimize neuro-symbolic AI algorithms for mission-critical, real-world use cases. Implement and evaluate hybrid AI models using large, real-world datasets. Ensure efficient, clean, and well-documented code following industry best practices. 3. Research & Innovation Collaborate with global research teams, academic institutions, and industry partners to advance neuro-symbolic AI methodologies. Publish and present technical findings at top AI conferences and journals. Lead technical ideation to enhance and evolve existing AI solutions. Required Qualifications Education: PhD in Computer Science, Artificial Intelligence, Data Science, or closely related field. Experience: Minimum 15 years in AI research, software development, and applied neuro-symbolic AI. Programming Expertise: Advanced proficiency in Python and Go, with hands-on experience using neuro-symbolic AI toolkits such as PyG, PyKEEN, and PyTorch. Domain Knowledge: o Deep understanding of knowledge representation, symbolic reasoning, and machine learning. o Strong background in graph neural networks, probabilistic logic, and hybrid AI architectures. Leadership & Soft Skills: Proven track record leading large-scale AI initiatives, with exceptional communication and cross-functional collaboration skills. Hands-on experience deploying AI systems on Azure. Familiarity with automated reasoning systems, logic programming, and explainable AI (XAI) principles. Experience with scalable microservices architectures for AI solutions.

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