We need a Software Engineer who loves messy data and wants to sit at the intersection of data pipelines, light ML Ops, and “glue code” that makes models actually work in production.
This is the person who lets the AI team move twice as fast by owning everything that happens before training and after training — schemas, cleaning, shaping, deploying, documenting.
Not an ML researcher.
Not a pure DevOps engineer.
A data-focused SWE who thrives in ambiguity and gets s*** done. You should be excited about working at a fast-faced startup, with an ownership mentality and a drive to build.
You Are
- Strong in Python and software engineering fundamentals
- Comfortable with large, inconsistent datasets
- Able to deploy code and debug pipelines
- Detail-oriented, fast, and scrappy
- Excited to work one sprint ahead of the AI team
Nice to have:
ML Ops, DevOps, computer vision experience, startup experience, Boston.
Why Join
- Founding-team impact in a venture-backed company solving valuation and grading for multi-trillion-dollar asset classes.
- A chance to define how AI success is measured in markets that have never had rigorous, transparent metrics.
- Report directly to the founders (repeat founders, published AI research) — moving fast, breaking bottlenecks, and scaling across categories.
Top Skills
What We Do
Vardera is the intelligence layer that helps organizations understand, price, and move hard assets with confidence. From art and collectibles to industrial equipment and beyond, our computer vision and machine learning platform embeds expert-level assessment into any workflow—replacing bottlenecks with automation and guesswork with data.
We're a venture-backed team building foundational infrastructure for a defining moment: as $8+ trillion in hard assets transfers between generations and industries that have relied on offline expertise for centuries finally go digital.
Why Work With Us
Greenfield AI at the ground floor. You're not patching legacy systems—you're architecting from scratch. Small team means your code ships and matters. We're defining how an entire industry operates, not competing in a crowded market. Early-stage impact, interesting problems, real ownership.
Gallery
