We are empowering people to go from concepts to construction within hours, enhancing collaboration in the world of atoms & pushing the boundaries of what’s possible, for humanity over the next few decades.

For phase 1, we're training foundational AI models that create building code-compliant BIM models, cost analysis & documentation from 2D building blueprints.

We are a small team of 20+ and looking for people passionate about 3D generation/reconstruction.

We’re targeting $100B+ opportunity in construction’s design, estimation, and planning software—ripe for disruption by AI-first platforms.

If you're interested in joining an early stage AI startup building foundational models, geometric and physics engines from scratch to transform how the world designs and builds infrastructure, with real autonomy and the resources to solve hard problems, apply or reach out to us today.

About the role

Augrade 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

• 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.

• 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 the model execution, performance on different platforms, GPU, CPU etc.

• Experiment & apply strategies for continuous learning in the context of 3D data, enabling AI systems to adapt and improve over time

• 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)

• 7+ yrs experience OR some really cool (technically) projects.

• Strong expertise in GNN frameworks and architectures.

• Experience with RL (Reinforcement learning)

• Strong understanding of 3D environments.

• Strong skills in data & database management.

• 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

• Ability to work comfortably with computations graphs and IRs (compiler background a strong bonus)

• Deep understanding of modern vector/embedding-based graph representation techniques with proven experience in designing and implementing algorithms for their generation

• Enjoy collaborating within and across teams

• Fast learner.

Good to have

• Experience with LLMs, convex optimization, and physics-based simulation.

• Robust knowledge and experience in implementing graph analytics solutions in distributed systems, including community detection/understanding, pattern matching, sub-graph extraction, and importance ranking

• Experience in Architecture, Aerospace, or Automotive industries

Benefits

• Competitive compensation & ESOPs

• Generous PTO / sick leave

• Visa sponsorship (For select few candidates)

• And more as the team grows