Computer Vision Engineer

Há 7 dias

Santa Catarina, Brasil Talent Global LLC Tempo inteiro US$60.000 - US$120.000 por ano

Computer Vision Engineer

Location:
Remote

Schedule:
9:00 AM – 5:00 PM (client's local time)

About This Role:

The client company is an art dealer. This role will help potential buyers better identify the specific artwork by uploading photos. The client company has an existing artwork database and a cross-reference system. They are hiring a computer vision engineer to improve the accuracy of the existing system.

Responsibilities:

  • Learn how the current image-matching system works and how customers use it.
  • Measure today's accuracy (e.g., how often the top matches are correct) and agree on targets.
  • Review failed or low-confidence matches, spot patterns (lighting, angle, crop, card condition), 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.

Qualifications:

  • Proficient in using a MacBook.
  • C1 English level above.
  • 3+ years of hands-on computer vision/ML experience (or equivalent projects), 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., FastAPl/Flask, Docker); familiarity with cloud platforms (AWS/GCP/Azure).

Preferred Qualifications:

  • Experience with
    ANN/vector search
    (FAISS, ScaNN, Milvus, Annoy) and vector store design.
  • Knowledge of multimodal or self-supervised models (e.g., CLIP, SimCLR), image dedup/perceptual hashing, and hard-negative mining.
  • Familiarity with MLOps tools (
    MLflow/DVC
    , Airflow/Prefect) and real-time monitoring for drift/quality.
  • Background in e-commerce, collectibles, or other large-catalog visual search domains.
  • Comfort optimizing inference (quantization, batching, ONNX/TensorRT) and reducing latency at scale.

Payment is in USD.

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