AI/Generative design Developer

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

# AI/Generative design DeveloperAugrade · San Francisco, United States## DetailsEmployer: AugradeLocation: San Francisco, United StatesWork type: In personPosted by employer: 29 Sep 2026Added here: 29 Sep 2026Listing last seen: 1 Oct 2026Skills / tags: Generative DesignApply: Apply on employer site## AboutAugrade is on a mission to enable Humans to build infrastructure on Earth & Beyond. Augmenting human capabilities & civilization by empowering the technical & non-technical users to design, predict costs & schedules of construction projects.You will be working directly on all our GNN efforts such as building architectures & modules, working on graph structures extensively to identify, represent & modify various elements, properties, hierarchies etc. You will be a part of the core GNN team & working closely with other teams to Augment Human Capabilities. If you resonate with the mission & are passionate about solving the hard problems relentlessly, aren’t afraid to try the bold ideas & fail (most of the times), this is the perfect role.What you’ll do [li indent=0 align=left]Develop and apply advanced graph neural network models to identify, verify & modify complex structural assemblies and component representations of detailed 3D models including but not limited to apartments, data center, hospitals & manufacturing sites.[li indent=0 align=left]Develop GNNs for identification, hierarchical representation, modification and verification of 3D model meshes, topology etc.[li indent=0 align=left]Understand and improve the effect of computational graph representation on the model execution, performance on different platforms, GPU, CPU etc.[li indent=0 align=left]Experiment & apply strategies for continuous learning in the context of 3D data, enabling AI systems to adapt and improve over time[li indent=0 align=left]Research and experiment with emerging technologies and tools in the graph and AI domains, ensuring Augrade’s solution stays ahead of the curve About you (Qualifications etc) [li indent=0 align=left]7+ yrs experience OR some really cool (technically) projects.[li indent=0 align=left]Strong expertise in GNN frameworks and architectures.[li indent=0 align=left]Experience with RL (Reinforcement learning)[li indent=0 align=left]Strong understanding of 3D environments.[li indent=0 align=left]Strong skills in data & database management.[li indent=0 align=left]Experience with knowledge graph stores such as Neo4j (or its equivalent TigerGraph, Neptune, etc), and surrounding semantic technology (OWL, RDF, SWRL, SPARQL, JSON-LD) is a significant plus[li indent=0 align=left]Ability to work comfortably with computations graphs and IRs (compiler background a strong bonus)[li indent=0 align=left]Deep understanding of modern vector/embedding-based graph representation techniques with proven experience in designing and implementing algorithms for their generation[li indent=0 align=left]Enjoy collaborating within and across teams[li indent=0 align=left]Fast learner. Good to have [li indent=0 align=left]Experience with LLMs, convex optimization, and physics-based simulation.[li indent=0 align=left]Robust knowledge and experience in implementing graph analytics solutions in distributed systems, including community detection/understanding, pattern matching, sub-graph extraction, and importance ranking[li indent=0 align=left]Experience in Architecture, Aerospace, or Automotive industries Benefits [li indent=0 align=left]Competitive compensation & ESOPs[li indent=0 align=left]Generous PTO / sick leave[li indent=0 align=left]Visa sponsorship (For select few candidates)[li indent=0 align=left]And more as the team grows