AI & Graph Neural Network Design Engineer (3D)

Computationaldesign; San Francisco (CA); On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

Competitive compensation

ESOPs

Visa sponsorship

Job summary

Augrade is seeking an experienced AI/ML engineer focused on graph neural networks to advance 3D model understanding across buildings and facilities. You will build sophisticated GNNs for complex structures and collaborate with multiple teams to push 3D vision capabilities forward.

You’ll apply cutting-edge graph analytics, explore reinforcement learning and vector embeddings, and contribute to scalable AI in infrastructure design across diverse domains.

Qualifications

• 7+ yrs experience OR strong completed projects in GNNs.
• Strong expertise in GNN architectures.
• Experience with RL (Reinforcement learning).
• Strong understanding of 3D environments.
• Experience with data and database management.
• Knowledge graph stores such as Neo4j/TigerGraph/Neptune and related semantic tech is a plus.
• Experience with vector/embedding-based graph representations and algorithms.

Responsibilities

• Develop and apply advanced graph neural network models to identify, verify & modify complex structural assemblies and component representations of detailed 3D models.
• Develop GNNs for identification, hierarchical representation, modification and verification of 3D model meshes, topology etc.
• Understand and improve the effect of computational graph representation on model execution and performance on GPU/CPU.
• Experiment & apply strategies for continuous learning in the context of 3D data.
• Research and experiment with emerging graph/AI technologies to keep Augrade ahead.

Skills

GNN frameworks

Reinforcement learning

3D environments

Data management

Vector embeddings

Team collaboration

Tools

Neo4j

TigerGraph

Neptune

OWL

RDF

SWRL

SPARQL

JSON-LD

Job description

Augrade is seeking an experienced AI/ML engineer focused on graph neural networks to advance 3D model understanding across buildings and facilities. You will build sophisticated GNNs for complex structures and collaborate with multiple teams to push 3D vision capabilities forward.

You’ll apply cutting-edge graph analytics, explore reinforcement learning and vector embeddings, and contribute to scalable AI in infrastructure design across diverse domains.