5 дней назад
Senior AI/ML Engineer
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior AI/ML Engineer (Search and Recommendations): Building ranking, recommendation, and multimodal search systems for a global jewellery marketplace with an accent on information retrieval, learning-to-rank, embeddings, and LLM-powered discovery. Focus on owning production ML systems end to end, designing low-latency model serving, evaluating probabilistic outputs, and building graceful recovery paths for confidently wrong results.
Location: Remote in the US; Boston or NYC
Company
operates a digital marketplace connecting diamond and gemstone suppliers with jewellery retailers across more than 70 countries.
What you will do
- Build and operate search, ranking, recommendation, and multimodal retrieval systems for 's marketplace and branded jeweller storefronts.
- Develop contextual and conversational search using language models, prompt design, and retrieval-augmented approaches.
- Build image-to-attribute and image-to-product-match pipelines using image embeddings.
- Own ranking and recommendation models across feature development, training, evaluation, deployment, and monitoring.
- Design low-latency real-time model-serving systems and multi-tenant configurable infrastructure.
- Define ranking-specific evaluation with offline metrics, interleaving experiments, stress testing, and recovery paths for probabilistic failures.
Requirements
- 5–10 years of experience in applied machine learning, information retrieval, ranking, recommendations, or related engineering work.
- Experience with real search infrastructure such as Elasticsearch, OpenSearch, Vespa, pgvector, Pinecone, or Weaviate.
- Hands-on experience with learning-to-rank, embedding-based retrieval, collaborative filtering, and the full production model lifecycle.
- Production experience with NLP, LLM applications, prompt design, retrieval-augmented approaches, and evaluation of model output.
- Experience building low-latency model-serving systems, image-embedding pipelines, or conversational search products.
- Ability to design systems that handle probabilistic failures, support multiple tenants, and maintain rigorous testing and evaluation discipline.
Nice to have
- Background in marketplace or e-commerce search, ranking, or recommendations.
- Experience with computer vision fundamentals and image-to-product matching.
- Experience using AI coding agents to build ML infrastructure and pipelines.
Culture & Benefits
- Remote-first culture with flexible working hours.
- Ownership and empowerment in a collaborative, high-growth environment.
- Opportunities for learning and professional growth.
- Unlimited holiday allowance.
- Equal opportunity workplace welcoming applicants from diverse backgrounds.
Applications should include a CV in English.
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