Vision Expert

1 dia atrás

Santa Catarina, Brasil beBeeComputer Tempo inteiro US$150.000 - US$200.000
Improve Image Matching Systems

This role will help potential buyers better identify specific artworks by uploading photos to an existing artwork database and cross-reference system. We are looking for a skilled computer vision expert to improve the accuracy of our current image-matching system.

We are seeking someone with expertise in using machine learning algorithms to analyze images, extract relevant features, and match them efficiently.

A successful candidate should have hands-on experience with deep learning frameworks such as PyTorch or TensorFlow, along with OpenCV and scikit-image.

The ideal candidate will also have a solid understanding of embeddings (CNNs/ViT), loss functions (contrastive/triplet), and evaluation for retrieval tasks.

We expect the chosen candidate to be proficient in SQL for data analysis, validation, and performance investigations.

Responsibilities:
  • Learn how the current image-matching system works and understand customer usage patterns.
  • Measure today's accuracy and agree on targets.
  • Review failed or low-confidence matches, spot patterns, and prioritize fixes.
  • Improve accuracy by testing small, safe changes—model settings, thresholds, and data tweaks—and keep what works.
  • Strengthen the data: add missing examples, correct labels, and create better test sets.
  • Tune search and matching rules to reduce false matches without hiding correct ones.
  • Run A/B or side-by-side tests, compare results, and clearly report what improved.
  • Ship changes with minimal risk, monitor results after release, and roll back if needed.
  • Build simple dashboards/queries (including SQL) to track accuracy and user impact over time.
Requirements:
  • Proficient in using a MacBook.
  • 3+ years of hands-on computer vision/ML experience, including training and deploying models to production.
  • Strong Python skills and proficiency with one major DL framework (PyTorch or TensorFlow), plus OpenCV / scikit-image.
  • Demonstrated work in image retrieval/reverse image search, metric learning, or similarity matching at scale.
  • Solid understanding of embeddings (CNNs/ViT), loss functions (contrastive/triplet), and evaluation for retrieval tasks.
  • SQL proficiency for data analysis, validation, and performance investigations.
  • Experience shipping models behind services (e.g., FastAPI/Flask, Docker); familiarity with cloud platforms (AWS/GCP/Azure).

This is a great opportunity for a motivated individual to contribute to the development of our image-matching system and improve the overall user experience.

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