AI-powered design tool for real world product designers and their teams. Go from sketch to photorealistic 3D render in seconds. Start creating for free. Backed by Index and AI Grant.
About the role
As an ML Data Engineer , you'll build and improve the systems that turn professional design work into training-grade preference data and training results back into a better product.
What they're looking for
- Experience building data infrastructure, ML data systems, or production data pipelines used by other teams
- Strong software engineering skills and experience building reliable production systems
- Experience designing data models and pipelines with reproducibility, observability, and lineage in mind
- Comfort working with large or complex datasets and debugging issues across multiple parts of a data system
- An experimental mindset and comfort working closely with researchers to turn ambiguous questions into measurable datasets
- Good judgment around data quality, including an understanding of when the absence of a signal is meaningfully different from a negative signal
More about this role
Applying to this role will also allow us to consider you for other research opportunities at Vizcom. We believe the best roles are shaped around exceptional people, not just job descriptions.
Vizcom is where design teams at companies like Nike, GM, New Balance, and Hasbro bring ideas from sketch to product. Designers use Vizcom to sketch, render, explore color and materials, work in 3D, and prepare concepts for production.
The render itself was never the point. The point is the physical thing that comes after it. We call this pencil to product .
Vizcom is a Series B company with more than $52M raised.
More than 700,000 designers have worked in Vizcom, and every session leaves a trail: candidates selected, outputs promoted into designs, regions masked and renamed, and entire directions kept or discarded.
That trail is one of the most valuable things we create outside of the product itself. Today, though, it's more archaeology than asset. Only a fraction of what happens in a session reaches training-grade quality, while increasingly sophisticated post-training methods depend on exactly this kind of high-quality, domain-specific data.
Your job will be to help turn that trail into a...
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