Senior Graph Intelligence Architect

Experience : 6.00 + years

Salary : USD 3216-6432 / month (based on experience)

Expected Notice Period : 15 Days

Shift : (GMT+05 : 30) Asia / Kolkata (IST)

Opportunity Type : Remote

Placement Type : Full Time Contract for 12 Months(40 hrs a week / 160 hrs a month)

• Note : This is a requirement for one of Uplers' client - AI industry)

What do you need for this opportunity

Must have skills required :

PyTorch, Convolutional Neural Networks, Deep Learning, graph neural networks, Neurosymbolic AI

AI industry is Looking for :

Senior Graph Intelligence Architect

Contract Duration : 12 Months

About Company

This company is pioneering the next generation of enterprise artificial general intelligence through revolutionary knowledge

sculpting technology. We are building the critical infrastructure that enables organizations to transform their collective

intelligence into precise, explainable, and trustworthy AI systems. Our platform bridges the gap between human

expertise and machine reasoning, creating organizational AGI that operates with unprecedented accuracy and

transparency.

We are at the intersection of knowledge graphs, neural reasoning, and enterprise AI - solving one of the most

important challenges in artificial intelligence today.

The Role

We are seeking a Senior Graph Intelligence Architect to lead the development of our neurosymbolic AI architecture.

This is a founding technical role where you'll design and implement the graph neural network infrastructure that

powers our knowledge reasoning engine. You'll be working at the cutting edge of graph-based machine learning,

logical neural networks, and knowledge representation.

This role is perfect for someone who believes that the future of AGI lies not just in scale, but in the intelligent

combination of structured knowledge and neural reasoning.

Core Responsibilities

Graph Neural Architecture Development

 Design and implement graph neural network architectures for knowledge reasoning over enterprise-scale

knowledge graphs (millions of nodes / edges)

 Develop novel approaches for combining Graph Convolutional Networks (GCNs), Graph Attention Networks

(GATs), and Message Passing Neural Networks for ontological reasoning

 Build systems that can perform multi-hop reasoning and inference over complex organizational knowledge

structures

Neurosymbolic Integration

 Implement Logical Neural Networks (LNNs) or similar architectures that combine symbolic reasoning with

neural learning

 Design hybrid systems that maintain explainability while leveraging deep learning capabilities

 Create bidirectional bridges between formal ontologies (OWL / RDF) and neural representations

Knowledge Graph Intelligence

 Develop graph embedding techniques optimized for enterprise knowledge representation

 Implement knowledge graph completion and link prediction algorithms

 Design temporal graph networks for handling evolving organizational knowledge

 Build graph-based anomaly detection for identifying knowledge conflicts and gaps

Scalable Graph Computing

 Architect distributed graph processing systems handling billions of edges

 Optimize GNN training and inference for production environments

 Implement efficient graph sampling and batching strategies for large-scale graphs

 Design real-time graph update mechanisms for continuous knowledge evolution

Research & Innovation

 Stay current with latest advances in geometric deep learning and neurosymbolic AI

 Contribute to research papers and patents in graph-based AGI

 Evaluate and integrate cutting-edge approaches from papers into production systems

Required Qualifications

Educational Background

 PhD in Computer Science, Machine Learning, or related field with focus on graph neural networks,

knowledge graphs, or neurosymbolic AI

 OR MS with 5+ years of exceptional industry experience in graph-based machine learning

Technical Expertise

Graph Neural Networks

 Deep expertise in GNN architectures (GCN, GAT, GraphSAGE, GIN, PNA)

 Experience with geometric deep learning frameworks (PyTorch Geometric, DGL, Spektral)

 Knowledge of graph pooling, graph generation, and graph-to-graph translation

Knowledge Graphs & Reasoning

 Hands-on experience with graph databases (Neo4j, TigerGraph, Amazon Neptune, or similar)

 Understanding of ontologies, RDF, OWL, and SPARQL

 Experience with reasoning engines and rule-based systems

 Knowledge graph embedding methods (TransE, ComplEx, RotatE, etc.)

Neural Network Architectures

 Experience with Logical Neural Networks, Neural Theorem Provers, or similar neurosymbolic approaches

 Understanding of attention mechanisms and transformers for graphs

 Experience with CNN architectures adapted for graph-structured data

Programming & Tools

 Expert-level Python with deep learning frameworks (PyTorch preferred)

 Experience with distributed computing (Ray, Spark, or similar)

 Graph processing frameworks (NetworkX, igraph, RAPIDS cuGraph)

 Production ML deployment (MLflow, Kubeflow, or similar)

Preferred Qualifications

 Publications in top-tier conferences (NeurIPS, ICML, ICLR, KDD, WWW)

 Experience with enterprise knowledge management systems

 Background in formal logic, description logic, or automated reasoning

 Experience with large language models and their integration with knowledge graphs

 Contributions to open-source graph ML projects

 Experience with GPU-accelerated graph algorithms

How to apply for this opportunity

About Uplers :

Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement.

(Note : There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well).

So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Skills Required

Distributed Computing, Sparql, owl, graph databases , Deep Learning, Pytorch, Rdf, Python