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Nivoda
Nivoda
201 – 500 Angajați
Comerț cu amănuntulComerț electronicPiață online
Nivoda operează o piață de diamante și pietre prețioase destinată comercianților de bijuterii. Platforma le oferă acces la diamante naturale, diamante cultivate în laborator și pietre prețioase, precum și instrumente pentru a-și extinde oferta din magazinele fizice și online. Showroomurile virtuale și fluxurile de diamante îi ajută să prezinte pietrele clienților fără să păstreze în stoc întreaga gamă. Nivoda coordonează, de asemenea, controlul calității și logistica și oferă livrare rapidă și condiții flexibile de creditare ca parte a soluțiilor sale pentru comerțul cu amănuntul.
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Senior AI/ML Engineer, Remote in the United States

Develop ranking, recommendation, and multimodal search systems for Nivoda’s global jewellery marketplace and jeweller storefronts. Build production machine learning capabilities across search, product discovery, and image matching.

USStatele Unite ale AmericiiMAMassachusettsNYNew YorkRemoteNormă întreagăSeniorLimbă Obligatorie: englezăInginer de învățare automată
Elasticsearch

Descriere

  • Build and run marketplace search infrastructure for ranking and multimodal search.
  • Create configurable, multi-tenant ranking and recommendation systems for Nivoda’s marketplace and jeweller storefronts.
  • Develop contextual search and a planned conversational assistant with prompt design and retrieval-augmented methods.
  • Create image-to-attribute and image-to-product matching pipelines using image embeddings.
  • Add recovery paths and confirmation steps before probabilistic systems take high-stakes actions.
  • Define and conduct search and ranking evaluations, including offline metrics and interleaving experiments.
  • Assess and stress-test foundation model and LLM outputs.
  • Manage ranking and recommendation models through feature development, training, evaluation, deployment, and monitoring.
  • Design and optimize real-time model serving for low latency under production load.
  • Use AI coding agents to develop ML infrastructure and pipelines, supported by rigorous evaluation harnesses.
  • Join the Discovery Pod to build ranking, recommendations, search input, contextual and conversational search, and image-upload search for a global jewellery marketplace.

Cerințe

  • 5–10 years of professional experience.
  • Experience with information retrieval infrastructure such as Elasticsearch/OpenSearch, Vespa, or vector databases including pgvector, Pinecone, or Weaviate.
  • Applied machine learning experience in ranking and recommendations, including learning-to-rank, embedding-based retrieval, and collaborative filtering.
  • Experience managing ML models across feature development, training, evaluation, deployment, and monitoring.
  • Production experience with NLP and LLM applications, including prompt design, retrieval-augmented methods, and handling zero-result and trade-off scenarios.
  • Experience serving models in low-latency, real-time systems under production load.
  • Ability to evaluate search and ranking systems using offline metrics and interleaving experiments.
  • Hands-on experience with foundation models and LLMs, including assessing and stress-testing their outputs.
  • Experience designing graceful failure handling for probabilistic systems.
  • Comfort using AI coding agents to build ML infrastructure and pipelines, with a strong commitment to evaluation and testing.
  • English-language CV.
  • Preferred: knowledge of computer vision fundamentals and image embeddings.
  • Preferred: experience designing configurable, multi-tenant systems.
  • Preferred: experience with conversational or assistant-style search products.
  • Preferred: experience with marketplace or e-commerce search, ranking, or recommendations.

Beneficii

  • Flexible working hours.
  • Remote-first culture.
  • Opportunities for professional growth and learning.
  • Unlimited holiday allowance.
  • Opportunity to join during a period of rapid expansion.

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