Neuro-Symbolic AI Manager

Job Title: Neuro-Symbolic AI Manager
Location: Redmond, WA (initial Remote can be discussed during interview)
Job Type: Contract (12+ Months, likely extension)

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.