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We recruit ML Talent for AI-Tech Startups
Applied Researcher | Machine Learning | Computer Vision | Generative Models | PyTorch | PBR Rendering | Multi-view Learning | Photometric stereo
About the Project
We're developing a machine learning pipeline that predicts high-quality material maps (diffuse, roughness, specular, metallic, normals) directly from photogrammetry images, eliminating the need for flash photography and manual input. This work is supported by a unique dataset of physically accurate, real-world scans that allow us to push well beyond the limits of most artist-created datasets.
As part of this effort, we're seeking a machine learning researcher to help bring this "image-to-material" pipeline to life, transforming how digital textures are created at scale.
Your Role and Impact
As a Machine Learning Applied Researcher, you’ll lead the development of core models that power this technology and contribute to fast-paced, product-focused innovation.
You will:
* Design and prototype generative models to predict material maps from real-world input
* Work with architectures such as U-Net, transformers, and diffusion models
* Develop training strategies for consistent results across multiple image views
* Collaborate with a cross-functional team to productionize research models
Key Responsibilities
* Build and train models to predict physically based rendering (PBR) maps from image data
* Explore methods for multi-view learning and cross-view consistency
* Leverage pretrained vision-language models (e.g., CLIP, DINO) for semantic alignment
* Use our proprietary real-world dataset to improve model generalization and realism
* Evaluate model performance on visual fidelity, accuracy, and generalizability
* Support research infrastructure and design new experiments from real data
* Present findings internally and help guide R&D strategy
* Integrate semantic context into predictions to improve cross-surface performance
* Stay engaged with the academic community and help identify research partnerships
Requirements
* Solid research background in computer vision or generative modeling (publications or thesis a plus)
* Experience with multi-view learning, inverse rendering, or 3D-aware models
* Proficiency in PyTorch and clean, maintainable ML code
* Hands-on experience working with large-scale image datasets and training pipelines
* Fast-moving, experiment-driven mindset with strong execution skills
Nice to Have
* Familiarity with rendering pipelines or 3D graphics tools (e.g. Blender, glTF, EXR workflows)
* Experience with material estimation, photogrammetry, or UV workflows
* Understanding of self-supervised learning (e.g., CLIP, DINO)
* Previous work involving physically based rendering or material scanning
* Contributions to open-source ML tools or frameworks
What We Offer
* An opportunity to shape the future of 3D content creation
* Work with some of the world’s most innovative studios in film, games, and design
* A fast-moving environment with real impact, autonomy, and room for growth
* Collaborative culture across engineering, research, and creative teams
* Competitive salary and equity package
Applied Researcher | Machine Learning | Computer Vision | Generative Models | PyTorch | PBR Rendering | Multi-view Learning | Photometric stereo
Seniority level
* Seniority level
Mid-Senior level
Employment type
* Employment type
Full-time
Job function
* Job function
Information Technology
* Industries
Technology, Information and Media
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