Computer Vision Engineer
Content + Source + Freshness • 17 Dec 2025 • 95% confidence
Offer value
Strong value due to competitive compensation, innovative work environment, and career-shaping opportunities in a cutting-edge field.
- Competitive salary: $175,000 - $250,000/year
- Innovative startup environment with rapid learning opportunities
- Direct impact on new technology applications
- Requires strong expertise in computer vision
Pros
- High salary range ($175,000 - $250,000) for engineers in a niche tech sector.
- Direct involvement in shaping innovative AI applications in the collectibles market.
- Rapid prototyping and exposure to advanced technologies.
Cons
- Startup environment may lead to instability and increased pressure.
- Requires strong expertise in computer vision which may limit applicant pool.
- Hybrid work model might not suit those preferring fully remote positions.
Who it's for
Mid to Senior Level • Hybrid with in-office expectations
Good fit
- Experienced computer vision engineers
- Tech innovators eager to shape new markets
- Candidates comfortable in a startup culture
Not recommended for
- New graduates lacking relevant experience
- Individuals preferring stable corporate settings
- Those reluctant to work with high expectations under pressure
Motivation fit
Key skills
About the job
Company Description
Vardera Labs is building the next generation of infrastructure for the art, auction, and collectibles industry by utilizing cutting-edge AI, computer vision, and automation. Our solutions empower auction houses worldwide by streamlining catalog creation, data strategy, and operational excellence. We are a small, venture-backed team with a bold mission to modernize a multi-billion-dollar market during a critical moment of generational ownership transfer and digital transformation.
What You’ll Do
- Design and deploy computer vision systems that identify, grade, and authenticate physical assets across categories like coins, comics, jewelry, and fine art.
- Build and fine-tune multimodal models that combine visual, textual, and structured data to deliver accurate, explainable outputs.
- Prototype rapidly: leverage foundation models, open-source frameworks, and custom training pipelines to reach production-ready performance quickly.
- Define and evolve accuracy and quality metrics beyond standard loss functions — optimizing for the real-world economics of error and trust.
- Create robust evaluation and monitoring pipelines that track performance by category, lighting condition, and visual defect type.
- Work directly with founders and customers to turn ambiguous problems into measurable, repeatable, high-accuracy solutions.
- 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
- Strong foundation in computer vision, deep learning, and applied ML (e.g., segmentation, detection, embedding models).
- Experience with modern CV toolkits — PyTorch, YOLO, SAM, Detectron, CLIP, or similar.
- Comfort working across image data pipelines, from annotation strategy to model deployment and feedback loops.
- Pragmatic engineer who balances rigor with velocity: knows when to experiment, when to productionize, and when “good enough” drives impact.
- Excitement to join a post-seed startup where model accuracy and innovation directly shape customer value.
Why Join
- Founding-team impact at a venture-backed company redefining valuation, grading, and authentication for multi-trillion-dollar asset classes.
- A chance to shape how computer vision and AI are applied to markets that have never had transparent or measurable standards.
- Work directly with experienced founders (repeat founders, published AI research) in a culture that prioritizes autonomy, rapid iteration, and tangible results.
Compensation
- Salary level matching seed-stage hires (relative to experience and fit): $175,000 - $250,000
- Equity: Meaningful early equity in a high growth startup
Location
- Hybrid with periodic in-person offsites and industry conferences. While we have a bias towards in person in Boston, it’s not required everyday, but expected you spend >50% of your time in the office.
