Lead Generative AI Engineer; Diffusion Models, 3D, VLM

Role Description

Edensign is building the future of AI-powered visual and spatial engine. Backed by the Harvard Innovation Labs, we’re creating next-generation intelligent systems that merge generative AI, 3D understanding, and spatial intelligence to transform how real-world spaces are visualized, staged, and experienced.

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Full-time | Preference for Boston based candidates

We’re looking for a senior technical leader to drive the development of our core AI engine. The ideal candidate has deep experience training large generative models
, including diffusion, 3D reconstruction networks, multimodal, VLM architectures. In this role, you will spearhead model training pipelines, R&D experiments, data strategy, and foundational architecture decisions.

This is an opportunity to help build the next generation of spatial AI - from multi-view consistency to 2D-to-3D-to-2D transformation and advanced scene understanding.

• Design, train, and optimize cutting-edge generative models, including diffusion, 3D reconstruction, and multimodal/VLM architectures
• Build and manage scalable training pipelines, data curation workflows, and experiment tracking
• Lead research experiments, benchmarking, and exploration of new modeling techniques
• Architect the evolution of our spatial AI stack—from prototyping new ideas to deploying production-ready models
• Collaborate with engineering and product teams to integrate AI capabilities seamlessly into real-world workflows
• Make strategic decisions around infrastructure, GPU utilization, model efficiency, and training optimization
• Contribute to Edensign’s long-term technical roadmap and innovation direction

• Strong expertise in training generative models (diffusion, GANs, 3D generative models, or scene-reconstruction networks)
• Deep background in Computer Vision
  , Computer Graphics
  , 3D geometry
  , NeRF-like architectures
  , or multi-view learning
• Familiarity with node-based generative tools (e.g.,
  ComfyUI
  ) is a plus
• Experience with VLMs, multimodal models, grounding, or spatial reasoning is highly valuable
• Proficiency in Python and modern ML frameworks
• Hands-on experience with distributed training, GPU optimization, and large-scale experiment management
• Ability to work independently and lead technical direction in a fast-paced startup environment
• Strong analytical, problem-solving, and system design skills
• Excellent communication and collaboration skills
• Master’s or PhD in Computer Science, AI/ML, Computer Vision, or a related field
• Experience in real estate, architecture, spatial design, or spatial computing is a bonus