Neuro-Symbolic AI Manager - Austin, TX - Hybrid Model Job at Gandiva Insights, Austin, TX

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  • Gandiva Insights
  • Austin, TX

Job Description

Role: Neuro-Symbolic AI Manager

Location: Austin, TX - Hybrid Model

Job Type: Long Term Contract

Job Description:

Key Responsibilities:

Algorithm Development & Implementation:

  • Design, develop, and optimize neuro-symbolic AI algorithms for real-world applications.
  • Implement and evaluate AI models using real-world data.
  • Ensure clean, efficient, and well-documented implementation of AI solutions.

Required Skills & Qualifications:

Education: PhD in Computer Science, Artificial Intelligence, Data Science, or a related field.

Experience: 15+ years of experience in AI research, software development, and neuro-symbolic AI applications.

Programming Expertise: Strong proficiency in Python, Go, and related AI toolkits.

Experience with neuro-symbolic AI frameworks such as PyG, PyKEEN, PyTorch.

Research & Innovation:

Lead technical discussions and ideation to enhance existing solutions.

Collaborate with global research teams to advance neuro-symbolic AI methodologies.

Leadership & Collaboration:

Provide technical mentorship to AI researchers, engineers, and data scientists.

Drive collaborations with academic and industry partners for AI advancements.

Shape AI strategies and innovation roadmaps for product and service development.

Domain Knowledge:

In-depth understanding of knowledge representation, symbolic reasoning, and machine learning.

Strong grasp of graph neural networks, probabilistic logic, and hybrid AI models.

Technical & Soft Skills:

Proven ability to lead AI-driven projects from research to production.

Excellent communication and collaboration skills to engage with multidisciplinary teams.

Preferred Qualifications:

Hands-on expertise in cloud-based AI deployment (AWS, Azure, or GCP).

Familiarity with automated reasoning systems, logic programming, and explainable AI (XAI).

Job Tags

Full time, Contract work, Part time, Seasonal work,

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