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Interested in this role? Email us at [email protected]

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About Vardera Labs

Vardera Labs is building the next generation of infrastructure for the art, auction, and collectibles industry—combining cutting-edge AI, computer vision, and automation to power catalog creation, data strategy, and operational excellence for auction houses worldwide. We’re a small, venture-backed team with a bold mission: to modernize a multi-billion-dollar market at a critical moment of generational ownership transfer and digital transformation.

What You’ll Do

• Take raw, messy datasets (images, text, auction results, grading guides) and turn them into structured, production-ready models.
• Balance deep statistical rigor with fast-and-loose prototypes — knowing when to fine-tune a foundation model, when to build from scratch, and when to hack something together to get customer feedback quickly.
• Define and evolve success metrics: go beyond accuracy to create domain-aware, cost-sensitive measures of error that reflect the real impact on customer workflows and revenue.
• Build reporting and monitoring frameworks that track performance by cohort, category, and business outcome — not just model loss curves.
• Hustle on speed: ship usable models in days/weeks, not months, while stacking learnings into a long-term defensible data moat.

What We’re Looking For

• Background in applied ML and data science (multimodal, embeddings, error metrics, statistical modeling).
• Pragmatic scientist — cares less about academic benchmarks and more about minimizing wasted effort while maximizing real-world accuracy.
• Fluent in experimentation: can spin up quick tests, evaluate with the right metrics, and pivot without ego.
• Hungry to join a post-seed startup where every line of code and every dataset meaningfully moves the business.

Why Join