Job Description

Build the foundational models that will give AI agents true 3D understanding

Want to solve the fundamental challenge of how AI systems perceive and reason about 3D geometry?

This Lead Applied Scientist role puts you at the forefront of creating perception capabilities for the next generation of agentic AI systems. You'll lead a team building discriminative and generative models introduced into agentic workflows, solving complex challenges in agentic AI for industrial applications.

You'll be joining a well-funded startup developing AI agents for advanced design and manufacturing workflows. Your work will bridge the gap between the physical world and intelligent reasoning systems, creating models that understand CAD data, meshes, and point clouds at a level that enables autonomous decision-making.

This role offers the opportunity to hands on lead a team to build 3D computer vision capabilities from the ground up. You'll be establishing an entirely new domain within the research team, with significant autonomy to define evaluation strategies, model objectives, and technical direction. Your models will form the perception backbone that enables agents to truly understand and manipulate the 3D world.

Your technical challenges:

• Build models that understand diverse 3D data types (CAD, mesh, point cloud) and learn transferable representations across formats
• Handle messy, lossy, or incomplete real-world data - moving beyond clean synthetic geometry to tackle industrial reality
• Scale training across multiple 3D tasks: segmentation, classification, correspondence, and eventually generation
• Create evaluation pipelines that meaningfully assess model performance and enable continuous production monitoring
• Work toward a foundational 3D model supporting both discriminative and generative tasks, integrated into broader agentic AI architecture

Your expertise should include:

• Deep specialisation in 3D computer vision (ideally including a PhD in Computer Vision)
• Strong knowledge of modern 3D architectures (PointNet++, MeshCNN, 3D Gaussian Splatting, diffusion models, VLMs)
• Proven ability training large-scale deep learning models with PyTorch
• Solid applied research skills - can implement novel architectures from papers and make them work in practice
• Experience with multimodal or vision-language model development

Nice to have:

• Background working with CAD data or industrial design workflows
• Experience in complex topics such as robotics, autonomous driving, or AR/VR with 3D perception focus
• Familiarity with SLAM, pose estimation, or differentiable rendering

You'll join a research team that values ownership and rapid iteration, with the resources to pursue ambitious technical goals. The company provides abundant compute resources and the freedom to explore foundational approaches whilst ensuring practical impact.

Package includes:

• Base salary: $300,000
• Performance bonus up to 20%
• Medical, dental, and vision coverage
• 401k with up to 3% company match
• 20+ vacation days

You'll need to be based in SF Bay Area or Miami, with a collaborative team environment that encourages innovation and technical excellence.

You must have valid right to work in the US without sponsorship (US Citizenship or Green Card).

If you're excited about creating the 3D perception capabilities that will power the next generation of intelligent agents, we'd love to hear from you.

All applicants will receive a response.