What are the responsibilities and job description for the AI Manager / Architect - Onsite position at CLIECON SOLUTIONS?
Job Details
Cliecon Solutions Inc, (head quartered in central NJ ) is one of the fastest growing and a leading consulting and management firm with 12 years of experience in Staff Augmentation. We handle complete recruiting cycle for fortune 500 clients, major implementing partners and tier -1 vendors. We specialized in recruiting for Application development, Big data, Databases, Infrastructure, Cloud, Mobile and ERP based solutions projects.
Position: AI Manager / Architect - Neuro-Symbolic
Location: Austin, TX
Duration: Long Term
Location: Austin, TX
Duration: Long Term
Required Skills :
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:
o Strong proficiency in Python, Go, and related AI toolkits.
o Experience with neuro-symbolic AI frameworks such as PyG, PyKEEN, PyTorch.
Domain Knowledge:
o In-depth understanding of knowledge representation, symbolic reasoning, and machine learning.
o Strong grasp of graph neural networks, probabilistic logic, and hybrid AI models.
Technical & Soft Skills:
o Proven ability to lead AI-driven projects from research to production.
o Excellent communication and collaboration skills to engage with multidisciplinary teams.
Preferred Qualifications:
Hands-on expertise in cloud-based AI deployment (AWS, Azure, or Google Cloud Platform).
Familiarity with automated reasoning systems, logic programming, and explainable AI (XAI).
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:
o Strong proficiency in Python, Go, and related AI toolkits.
o Experience with neuro-symbolic AI frameworks such as PyG, PyKEEN, PyTorch.
Domain Knowledge:
o In-depth understanding of knowledge representation, symbolic reasoning, and machine learning.
o Strong grasp of graph neural networks, probabilistic logic, and hybrid AI models.
Technical & Soft Skills:
o Proven ability to lead AI-driven projects from research to production.
o Excellent communication and collaboration skills to engage with multidisciplinary teams.
Preferred Qualifications:
Hands-on expertise in cloud-based AI deployment (AWS, Azure, or Google Cloud Platform).
Familiarity with automated reasoning systems, logic programming, and explainable AI (XAI).
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
